AEC November / December 2024

Building Information Modelling (BIM) technology for Architecture, Engineering and Construction

BIM AUTOMATION How Augmenta uses AI to wire buildings, delivering 3D designs in just hours

Speckle matures Autodesk’s AI strategy Navigating generative design November /December 2024 >> Vol.134 p01_AEC_NOV24_Cover V3.indd 2

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Building Information Modelling (BIM) technology for Architecture, Engineering and Construction

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Industry news 6 Chaos targets architectural storytelling, Cintoo launches the Metaverse for reality models, V-Ray 7 supports Gaussian splats, plus lots more

AI in AEC news 12 Nemetschek to add AI layer to key AEC solutions, Trimble trumpets AI capabilities for AEC, Snaptrude unveils AI renderer, plus lots more

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With a new CEO, and an ever-broadening product suite, Graphisoft is focussed on extending its global footprint

Bentley: the promise of data freedom 34 When it comes to openness, few inspire as much confidence as Bentley in ensuring that customers retain control of their data

Cover story: Augmenta’s productivity promise 13 BHoM - addressing Augmenta has a brand-new product interoperability 38 that uses AI to help electrically wire up a BIM model of a building in hours

Gen AI: are you riskmanaged ready? 16 May Winfield explores the legal aspects of AI. How reliable is the information we get back? How confidential is the data we send? And what about copyright?

Finch untethered 18 Architects spend a lot of time designing and revising floorplans. Finch aims to reduce preliminary design time by 80%

Navigating the boom in generative design 22 How can AEC professionals choose the right tool to meet their needs?

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Graphisoft accelerates development 30

Autodesk charts its AI future 26 If 2023 was the year that Autodesk announced its ambitions for AI, 2024 was when it fleshed out some of the details. But there’s still a long journey ahead

This computational development project allows AEC teams to improve project collaboration and foster standardisation

Speckle matures 42 Speckle is replacing clunky file-based processes with powerful workflows that connect incompatible BIM tools

HP Build Workspace 44 HP’s new cloud platform boosts collaboration, streamlines site reporting, and uses AI to vectorise drawings

Dalux ‘Hygge’ 46 Dalux has built a broad platform to liberate design and construction data

Matterport goes Pro 48 Matterport is lowering the barrier to entry for reality capture, bridging the gap between laser scanners and photogrammetry

DraftSight 2025 50 At time when 2D CAD is in the spotlight, we look at this AutoCAD alternative from Dassault Systèmes November / December 2024

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THE FUTURE OF AEC technology www.nxtbld.com

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THE FUTURE OF AEC software development www.nxtdev.build

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News

Chaos unveils Envision for architectural storytelling

haos is gearing up for the beta launch of Chaos Envision, a new photorealistic real-time ray traced 3D assembly and animation tool, designed to help architects and visualisers streamline the process of architectural storytelling.

One of the key aims of the software is to enable architects to do the type of work that previously would have to be done by a viz specialist in expert tools like Autodesk 3ds Max or Unreal Engine. Scenes can be assembled from multiple sources, including vrscene exports from Enscape, V-Ray and Corona, with ‘no prep needed’.

“You can have the design in Revit and the terrain in 3ds max, or an interesting facade in Rhino, and then you can

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assemble everything in Envision,” says product manager, Ana Lyubenova.

According to Chaos, visualisation starts immediately, and original data is loaded directly and accurately, preserving the visualisation effort that’s done in the 3D creation tool, even as each scene evolves.

Once inside Chaos Envision, scenes can be enhanced with realistic animated humans, crowds, vehicles, custom behaviours, and vegetation, before videos are published using the ‘flexible and intuitive’ animation system.

Multiple design options can be presented to clients, through animated videos that transition between variations, phases, views, materials, times of day and more.

■ www.chaos.com/envision

NXT BLD & DEV to return in June 2025 EC Magazine has announced the return of its annual events - NXT BLD and NXT DEV - to the Queen Elizabeth II Centre in London on 11 and 12 June 2025. These back-to-back conferences continue to be a focal point for technology in the AEC sector, and present a unique opportunity for AEC professionals and software developers to chart the course of next generation BIM software.

“After 20 years of ‘BIM as a means to produce drawings’, we are entering a new era, where design software will actually aid the design process, automate repetitive tasks and deliver real productivity benefits. NXT BLD and NXT

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DEV brings everyone together to influence and guide that development and connect the agents of change,” said event director, Martyn Day. “We must break down the silos, disrupt the old workflows and rethink what BIM could be. Technologies like the cloud, expert systems, DfMA, autodrawings and of course AI/ML are going to impact company tech stacks, workflows, data management, collaboration, data lifecycle.

Meanwhile, software companies face business challenges as licence-count sales will be replaced by intelligent services and automation. NXT BLD and NXT DEV is the forum for that discussion.”

Allplan 2025 launches llplan, a Nemetschek company, has launched Allplan 2025, the latest release of its multidisciplinary BIM software. New features include AI-driven visualisation, automated design tools, and ‘seamless real-time collaboration’.

Allplan for AEC disciplines, which covers buildings and infrastructure, and Allplan Precast, for the design of structural precast elements, walls and slabs, are now joined by a new Allplan Civil edition, which enables the design of bridges and all types of civil structures.

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■ www.allplan.com

dConstruct integrates with ACC Construct Robotics, the Singapore-based developer of SLAMbased mobile mapping solutions including a backpack and wheeled robot, has announced that its d.ASH Xplorer platform is now integrated with Autodesk Construction Cloud (ACC).

Project teams can import 3D models from Autodesk Build, Autodesk Docs, or BIM 360 into d.ASH Xplorer to compare 3D point cloud scans with BIM data managed within ACC.

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■ www.dconstruct.co

■ www.nxtbld.com ■ www.nxtdev.build

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The Future of Software is Open At Bentley, we believe that data and AI are powerful tools that can transform infrastructure design, construction, and operations. Software must be open and interoperable so data, processes, and ideas can flow freely across your ecosystem and the infrastructure lifecycle. That’s why we support open standards and an open platform for infrastructure digital twins.

Leverage your data to its fullest potential. Learn more at bentley.com.

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© 2024 Bentley Systems, Incorporated. Bentley and the Bentley logo are either registered or unregistered trademarks or service marks of Bentley Systems, Incorporated or one of its direct or indirect wholly owned subsidiaries. Other brands and product names are trademarks of their respective owners. 07/24

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News

V-Ray 7 for 3ds max to get support for Gaussian splats

D5 Render 2.9 launches for real-time viz 5 Render 2.9, the latest release of the AECfocused viz tool, includes a new advanced terrain feature for sculpting ‘realistic, dynamic environments’ and a Phasing Animation tool to make it easier to visualise how a building is to be constructed.

Other new features include better 3D performance when working with large models, ‘Random Placement’ to help avoid uniform, repetitive patterns in scenes, and an improved AI Enhancer that allows users to enhance lighting, materials, and character details up to 6K resolution.

New assets include elderly and children character models, as well as over 160 new indoor and outdoor materials, such as tiles, fabrics, and surfaces.

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aussian splats, a technique which uses AI to create a rich 3D scene from a series of photos or videos, can now be rendered in the beta version of V-Ray 7 for 3ds Max. The technology enables users to place buildings within their real-world context, or integrate scanned objects directly into the 3D scene.

“We can get correct raytraced camera effects like motion blur, DoF and

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distortion, as well as proper interaction with other CG elements in the scene – reflections, refractions and matte/shadow surfaces,” explains Georgi Zhekov, Chaos.

The implementation works with Gaussian splats .PLY files produced by popular tools like Postshot, Polycam, Luma.ai, Kiri, nerfStudio etc. PLY files are imported through a V-Ray Gaussian Geometry node.

■ www.chaos.com/vray

SrinSoft boosts Autodesk interoperability utodesk has formed a partnership with SrinSoft to improve interoperability across a range of Autodesk and third-party CAD and BIM software tools. Through the agreement users can share, via ‘seamless cloud-based data transfer’ in Autodesk Construction Cloud (ACC), entire files or subsets of models.

The partnership makes use of BIMDeX, SrinSoft’s AI-powered interoperability

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HP updates LF printers

rendering engine, expanded block and style libraries, a new block family feature, professional-grade layouts, model versioning, an improved drawing experience, enhanced DWG/DXF import/ export and improved PDF export.

P has updated its entry-level large format printers, with the launch of the DesignJet T200/T600 Printer 2025 editions. The improved 24-inch and 36-inch printers are said to reduce energy consumption and plastics.

HP says the new DesignJets also deliver a ‘seamless printing experience’ thanks to the new HP Click Driver, which it claims is the most significant driver update for large format printers in 30 years. It enables real-print preview from any Windows 11 application, enabling AEC professionals to ‘print preview’ designs before printing with a view to avoiding reprints, unseen errors, and wasted print resources.

■ www.rayon.design

■ www.hp.com/designjet

platform, which has been integrated with Autodesk Data Exchange (DX) and ACC using Autodesk Platform Services (APS).

BIMDex supports a range of AEC, manufacturing and process plant software, including Autodesk Revit, Autodesk Plant 3D, Autodesk Civil 3D, AutoCAD MEP, Autodesk Inventor, DS Solidworks, PTC Creo, Tekla Structures, Autodesk Docs, and Microsoft Power BI. ■ www.srinsofttech.com

Rayon V2 launches for collaborative CAD ayon has released V2 of its cloud-based CAD tool that allows architects to collaboratively draft together in real time. The software comes with redlining and single-click link sharing built in.

Rayon V2 features a new UI, a new

■ www.d5render.com

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27/11/2024 12:39

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News

ROUND UP Trimble connectivity

Cintoo Metaverse launches for immersive reality models

Trimble has enhanced Trimble App Xchange to make it easier for software developers and construction contractors to build integrations between Trimble and other software solutions. Additionally, contractors can create custom integrations with ‘unique workflow automation’ ■ https://appxchange.trimble.com

ProjectSight lite Trimble has unveiled a free version of construction project management software Trimble ProjectSight, which provides a centralised environment to manage and share drawings, photos, specifications, submittals, punchlists and RFIs ■ www.trimble.com/projectsight

Plant performance Okana, the global built environment consultancy, has been awarded Innovate UK funding to further develop its onsite plant performance measuring software Aquila.

Aquila uses real time 4D mapping of plant equipment to review, analyse and predict performance onsite ■ www.okana.global

Enscape 4.2 Enscape 4.2, the latest release of the BIM-centric real-time viz tool, includes a new Revit Graphics Override, which allows users to see material and colour overrides in renderings defined by Revit Filters. Other new features include improvements to the software raytracing and artistic visual mode ■ www.enscape3d.com

NavVis IVION Reality capture platform, NavVis IVION, now has the ability to import BIM models for construction verification. ‘As-designed’ IFC models can be compared to ‘as-built’ point clouds and users can annotate issues and share with other stakeholders ■ www.navvis.com

360 degree capture The iGuide Planix R1 is a new 360-degree camera system from Planitar that incorporates Ricoh’s Theta X camera technology alongside a 2D LiDAR sensor to pair spatial data capture with high-res 360-degree visuals for documenting spaces in 3D ■ www.goiguide.com

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intoo has launched Cintoo

3D scans and 3D models are all streamed from the Cintoo Cloud in real time, at the same high mesh resolution as the source point cloud thanks to Cintoo’s TurboMesh high fidelity reality capture data to an engine. According to Cintoo, no preparation immersive environment.

The Cintoo VR Experience is one of two work or pre-production is required.

With the ‘teleportation camera’ users initial apps in the Cintoo Metaverse can teleport anywhere in the scene simply portfolio. The VR app, which runs on by pointing and clicking or navigating Unreal Engine and is cloud-connected to the Cintoo platform, is designed to extend between scan set up locations.

In VR, users can create annotations, Cintoo’s collaboration and decisiontake measurements and then sync making capabilities.

The software allows project managers, everything back to the Cintoo project.

“This is not just about visualisation; it’s engineers and installers to navigate reality models at a true-to-life 1:1 scale on about driving actionable insights, reducing costs, and improving operations,” said ‘almost any’ VR device, as well as Cintoo CEO Dominique Pouliquen. compare as-builts to as-designed by overlaying scans with 3D models.

■ www.cintoo.com a new product C Metaverse, portfolio designed to bring

Skema drives SketchUp/Revit workflow IM software startup, Skema, has introduced a new integration with SketchUp aimed at helping designers make use of SketchUp’s earlystage design capabilities to drive BIM workflows and Revit deliverables.

The integration allows designers to start massing in SketchUp, move into Skema for ‘block-and-stack’ planning, and return to SketchUp for design exploration of facades, rendering, energy use, lighting, and more.

According to the developers, Skema’s ‘BIM in Minutes’ feature allows users to move their designs into Revit at the push of a button, for construction documentation.

“We’re working to bridge the gap between SketchUp and a firm’s existing

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BIM workflows within Revit,” said Richard Harpham, co-founder of Skema.

“The new Skema for SketchUp extension empowers architects to transform their initial design concepts into precise, datarich BIM models faster—reducing rework, data loss, and coding.”

■ www.skema.ai/skema-for-sketchup

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AI spotlight www.aecmag.com/AI News

AI NEWS BRIEFS AI BIM renderer Snaptrude is adding an AI renderer to its browser-based BIM tool. According to the developers, the AI renderer recognises the geometry of models, understands scale, and is trained to understand context, foreground, background and material, so users have control over their renders ■ www.snaptrude.com

Sponsored by

Nemetschek to add AI layer to key AEC solutions

GHD AI report A report from global engineering consultancy GHD, titled “Generative AI: Transforming the AEC Industry,” highlights the potential of AI to revolutionise design, construction, and maintenance processes. It calls for the strategic adoption and ethical deployment of AI technologies ■ www.tinyurl.com/GHD-AI

AI architecture Pantheon AI, billed as the ‘world’s first AI-enabled architecture firm’, has emerged from stealth with $25m in funding. The team brings together technologists who built AI systems at Stanford AI Lab, Facebook, Caltech, and IBM Watson, and architects from firms including Gensler, SOM, and KPF ■ www.withpantheon.ai

Interior design AI rendering expert Ismail Seleit has released two LoRA models for interior design exploration — InteriorDesignerFlux, based on FLUX.1-schnell, and InteriorDesigner-XL, based on Stable Diffusion XL (SDXL). Seleit also offers AI models for generating visuals of architecture and physical models ■ www.form-finder.squarespace.com

BIM-to-AI tool Dewan Architects + Engineers, a global multidisciplinary design consultancy firm is working on Quible, a BIM-to-AI tool that uses deep learning and LLMs to enable ‘smarter, more precise’ designs and to enhance data analysis and decision-making ■ www.dewan-architects.com

AI CONTENT HUB For the latest news, features, interviews and opinions relating to Artificial Intelligence (AI) in AEC, check out our new AI hub ■ www.aecmag.com/AI

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he Nemetschek Group, which includes the Allplan, Graphisoft, Solibri, Bluebeam, and Vectorworks brands, has developed an AI layer that will be embedded in all of the Group’s major solutions from 2025.

The AI layer is modular and uses ‘secure cloud technology’ to process user requests.

It can understand natural language, enabling ‘fast and accurate responses’ while optimising the way users work with Nemetschek products. The AI layer will support a wide range of use cases, from

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design ideation to task automation.

Intelligent automation plays a central role by offering automated task execution, and adaptive project management.

Insight-driven decision-making is achieved through AI-powered data insights, which guide design processes and optimise decision-making.

Additionally, design augmentation allows AI to assist in design iterations, pattern creation, and scenario simulations, enabling more innovative and creative project outcomes.

■ www.nemetschek.com

Trimble trumpets AI capabilities for AEC rimble gave attendees of its annual Trimble Dimensions user conference an inside look at the company’s latest initiatives to incorporate AI into AEC workflows, including visualisation, reality capture, project management and takeoff.

For reality capture, Trimble is using AI to help process data more efficiently with automatic point cloud segmentation, classification and feature extraction in survey CAD software Trimble Business Center.

For visualisation, SketchUp Diffusion [Labs] is a generative AI-powered tool, available as part of the SketchUp Labs public beta program, that allows architects and designers to generate visualisations in seconds based on the active SketchUp viewport and a natural

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language text prompt or preset style.

For project management, ProjectSight includes a new drawing import feature that uses AI to read and extract critical drawing information for improved project visualisation.

For takeoff, Trimble LiveCount uses new AI functionality to automatically detect and count thousands of symbols on construction drawings with a view to saving contractors from hours of manual, repetitive and time-consuming tasks.

Trimble LiveCount includes the ability to automatically detect and count different types of receptacles and switches — the most common electrical items on drawings, helping electrical contractors create estimates faster, easier and more accurately.

■ www.trimble.com

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AI spotlight

Augmenta’s productivity promise There’s been plenty of hype surrounding the use of AI for AEC design, but so far we’ve seen little of substance. However, green shoots are starting to appear. Martyn Day caught up with Augmenta who has a brand-new product that can electrically wire up a BIM model in one go

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t is very difficult to gauge the impact of AI and Machine Learning (ML) on any specific AEC discipline. It’s made even harder when the applications that claim to be AI are in fact several different computing automation strategies compiled together, with AI contributing the least. This will remain the case for a long time as developers of automation tools will use the best / fastest computational strategies for the right problem, and AI may well not be the centre or main contributor to the magic you will see before your eyes. However, it will increasingly come into the mix.

We first talked with Augmenta in October 2022. At the time, the company didn’t have a shipping product but was making noises about the automation of building systems such as mechanical, electrical and plumbing (MEP). Many of the team, based in Toronto, Canada, were ex Autodesk-developers who were responsible for the generative design code that was impressively applied to Autodesk’s manufacturing-focused CAD tools - Fusion and Inventor. They had big

www.AECmag.com/AI

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ideas as to how generative design could be applied in AEC but couldn’t find any takers within that Autodesk division, so set up Augmenta and started working on the problem of building services.

I dream of wires Augmenta has ‘shipped’ its first cloud product, aimed at wiring up electrical components in BIM models. The software is currently limited to USA projects, as the team has coded in US standards first. It automates the routing and coordination of conduit systems across an entire building, through multiple floors based on user-defined rules, with the specification of device and panel locations, no-go zones and run schedules.

When the BIM (Revit) model is uploaded, Augmenta wires up all the electrical components, puts holes through walls for conduit, models everything in 3D, and provides an estimated cost. It’s possible to run several strategies at once and compare the price difference. Typically, this would take an expert days or weeks.

Augmenta does it in hours.

Once the electrical design is completed this can be exported to Revit for editing, detailing and clash detection. As the solution is in the cloud, development is ongoing and will eventually expand out to other countries.

Augmenta is simultaneously working on its auto-plumbing application which may come out this time next year. It will be possible to run a solve for both wiring and plumbing simultaneously. Eventually, when MEP is ready, Augmenta could do the whole lot in one pass. However, obviously the results need to be checked by a professional and perhaps altered for reasons not yet built into Augmenta’s system.

Augmenta is one of the poster children for BIM 2.0. These expert systems, which are coming to assist professionals, rapidly crush specification and detail design times.

HighArc (www.tinyurl.com/ higharc-AEC) is another example that has built an automated house detail designer and drawing production system for American residential house builders.

If you extrapolate what these applications can do today, ten years into the

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AI spotlight www.aecmag.com/AI News

Sponsored by

plumbing, we just run all that concurrently, so you have a full MEP system, that’s fully designed and coordinated, AEC: What kind of benefit will just based off high-level requirements.

Augmenta offer electrical engineers and We’re moving upstream.

Today the way that the industry works Revit workflows? is by prioritising some systems over othSzymanski: At the moment we’re not ers, so mechanical has top priority, like producing 100% perfect designs. There’s ducting over plumbing. Ducting has pristill the need for human cleanup involved ority over pressure piping and those at the detail level. The system might add together have priority over electrical, an extra bend here and there, and there because electrical can go up down around etc. So electrical is effectively just routing could be a self-collision somewhere.

We’re tracking all this and reducing around in whatever space it can find. It’s the incident of errors over time. Today why we started there because we can we will get you that initial population, solve that problem for them, without anyThoughts from the team will get you from a model that has noth- one having to be aware they’re using a To coincide with the launch of the new ing, to something that has 80% and cus- radically new way of designing their sysproduct we had a wide-ranging talk with tomers are going to have to clean up that tems. Once we get into mechanical and Francesco Iorio, CEO, Aaron Szymanski, model themselves. Over time the amount plumbing, we’re going to build those out co-founder and head of product, and of human intervention will reduce. We all at the same time and at once solve the kind of think of ourselves as like a same problem in three or four hours.

Matthew Hernandez, VP of Growth.

We understand that iteration is an Iorio spoke at AEC Magazine’s NXT self-driving car startup, trying to reduce important part of the process and must DEV conference in 2023 (www.tinyurl.com/ the amount of human intervention.

We have a broad scope for electrical, we support that feedback loop. Our system NXT-Iorio) and was part of our mainstage means you can go demonstration in through two full iter2024 showing a ations of the entire non-Revit BIM workWe don’t want to just speed people up - that’s just one building in a day as flow (www.tinyurl.com/ benefit - we literally want to transform the construction opposed to that hapnxt-workflow). pening over the industry and change the 25 years of no productivity of months.

AEC Magazine: gains that has plagued our industry for many reasons course Now [at the moment] Why did you start Matthew Hernandez, VP of growth with each iteration with electrical? it’s a whole rebuild, going from scratch Iorio: Electrical is actually the hardest from a technical per- cover a lot of the details like supports and every time which we know is not ideal, so spective. It may be easier in the sense couplings and we will eventually detail we’re looking at user-defined iteration, that electricity doesn’t fight gravity like that functionality providing a full BoM. whether users can lock parts of the design water but other than that, from a purely We can wire up a small hospital in just and keep everything else unlocked for the computational geometric perspective, it’s three hours - that’s the whole design - and next iteration. But we want to be able for by far the hardest because electrical sys- eventually we’ll get to the point where this to happen automatically. Every user there’s effectively no clean up. That means might load in a new background model tems are made from conduits.

The number of parts that need model- zero to fully detailed BoM, fully coordinat- and the outcome is that everything is the ling are even ten times what you need for ed, ready to build in just a couple of hours. same except for one duct. Our software should recognise that and assume MEP. We aren’t aiming to output a diagram or a high-level conceptual model. AEC: What data does Augmenta need to everything else is optimal.”

We want to output everything, some- start modelling electrical systems?

AEC: We suspect that the makers of thing that’s constructible. We generate miles of raceway in one shot. This isn’t Szymanski: Basically, there are three conduit, MEP and plumbing might be main inputs: Revit model with just the interested in Augmenta specifying their an assistant, it’s an automated system.

To do plumbing we will have to con- most basic setup in terms of electrical products? sider pressure, easiest transitions. You equipment, the conduit run schedule, need to consider pressure drops, differ- which defines your ‘tos an froms’ and Szymanski: We’re talking to the main proentials and we would have to do some what you want to run between that equip- viders of conduit, and there’s a bunch of conversations we’re having on that topic. simulation. And of course, you must ment, along with the design rules.

We really want to be able to get to the The most straightforward interest is that think about slopes for drains, which are point where it’s just requirements, just they want to be included in our default a constraint.

MEP, in terms of geometry and topolo- tell us how many lights are in the build- library, they want to be in that end BoM.” gy, is much easier if you think about it. ing, tell us what sort of loads are in difThere are these giant ducts that take up a ferent parts of the building, [then] we’ll AEC: How will you sell Augmenta? Is it lot of space but essentially with mechani- place the panels, we’ll pick the equip- a SaaS service, on demand? cal it’s all about performance. You need ment for you, we’ll route everything and Szymanski: “We have two ways to get to to think about flow rates, take into con- coordinate everything.

Once we have the mechanical and market at the moment. The first is we’re sideration thermal losses, noise, vibrafuture, you should be able to realise that the AEC design space is going to look very different. The levels of industry knowledge that will be built into ‘intelligent’ software will mean smaller teams will become highly productive, with automation perhaps completing 90% or more of each discipline’s detail work.

Add in ten years development of conceptual AI design tools, autodrawings, digital fabrication strategies and we have to consider very different tech stacks and team skills within AEC. From an initial concept, it could be hours or minutes to get a fully detailed model, with drawings and costings.

tion. It’s something that would apply computational fluid dynamics too.”

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offering design services through a partnership with ENG (www.engbim.com). ENG is the largest big modelling firm in the United States. We are now running our software on their entire pipeline, so they are still kind of the front end from a consulting model. With the back end of it we do the solution generation, make the user models and do the final editing on top of them and deliver those to our customers, but we’re not expanding that right now.

We have been using our software long enough to have actually built buildings.

Our first was an elementary school in Michigan, we have another school where construction kicks off soon too. We are just building a flywheel for ourselves, where we’re running on as many live projects as we can, learning and building a product to produce real value for the industry.”

AEC: How does Augmenta use AI/ML? Szymanski: We use a combination of methods; our solution generation pipeline combines machine learning and various algorithmics methods in different parts. Right now, from a machine learning perspective we’re training primarily not on customer sites or in customer models, but on our own models. So, for example, when we generate a design, we generate a number of designs, a user picks one of those and we record that preference. We start to learn what is a higher quality design and what is a lower quality design, and then obviously there’s where those additional edits are made.

We learn from those edits as well and all this is about driving internally a higher quality score reducing the amount of human intervention. So, there’s a machine learning component that’s really about fine-tuning our internal weights and biases to produce higher quality results. The other thing we are using machine learning for is site interpretation. We’re not training on customer sites, but we’re really interested in using machine learning to interpret the sites to understand what’s a bathroom, what’s an elevator shaft, so we’re starting to extract that context data sites so that there’s less and less human setup required at the front end.

The biggest challenge we face, and it’s no surprise at all, is how messy Revit models are. They are so inconsistently modelled; people are not using the right elements and categories correctly. It’s no surprise to anyone I know in the industry, but it causes a massive headache when you’re trying to www.AECmag.com/AI

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AI spotlight

symptoms not the problem. Ultimately, multidisciplinary firms using this technology will be able to estimate within a percent, which is incredible, which makes that available to the rest of construction lowest carbon emissions, embodied carAEC: To come out with a good solution for bon lowers construction costs etc.” a design, you really need to make sure you have a good quality BIM model to start Business model with. From talking with others, the rather All this automation could transform the random nature of quality and precision in way AEC firms work, but it also has a huge architect’s BIM models is a problem. potential impact on software firms. To date, software firms have charged per user per Hernandez: Unfortunately, too many licence, or token-based systems for usage people don’t see the value in model fideli- estimated over years. Automation systems ty or use the best practices and that’s per- are going to remove the need for many vasive in the industry. We see the way of licences of software that firms rely on changing this is by making people incred- today. And yes, while others will say there ibly more efficient than they are today by will be new jobs, the correlation between automating and optimising the design. automation and smaller design teams, and When you control the design, you con- fewer licences is going to have real consetrol virtually all the downstream work- quences in future decades. We asked how flows, even to the level of construction and software firms like Augmenta are reinventconstructability. We don’t want to just ing the software business model? speed people up - that’s j u s t one benefit Hernandez: Our product is still very, very early. It’s not our goal to go out and sell a bunch of SaaS licences.

The pricing model that we use is to we literally measure as closely as we can how much want to transform the value customers are construction industry and getting out of our softchange the 25 years of no producware. For example, like tivity gains that has plagued our the 60% increase in speed, industry for many reasons. with routing, modelling, coordiWhen you control the design, nation and then we take a small which is essentially the data from which everything else flows, you unlock advanc- percentage of that as a fee. So as our es in estimation, in procurement, in con- scope increases, our fee will increase, but struction in safety on the job site, because we would still be leaving the user, you can prefabricate more. We are part- whether that’s a services firm, an enginering with people who model well, are neering firm, or contractor with 90% of into prefabrication, and are willing to the value that we create. spend time to use our innovative tool fully so they’re the ones who are going to Conclusion become more efficient. We already know Augmenta is a fascinating addition to there’s a huge labour shortage gap in con- the design landscape and the team is takstruction, let alone to get into BIM VDC.” ing on some very big challenges - not just by discipline, but by country; not just AEC: When people think of AI in AEC, attacking incumbent systems and workthey tend to think of Midjourney. How flows, but by having to trial new busiis Augmenta different? ness models.

We hope the team’s opinions have Hernandez: Right now, customers are stirred some thoughts and ideas of your saving about 60% but that’s just literally own, as to what is coming down the pipethe tip of the iceberg. We’re working on line for this industry with automation. some incredibly hard challenges - geome- The key takeaway seems to be that for try, clashes coordination, path choosing, the AEC industry to fully reap the downall in 3D. This is very different to the stream benefits of these advancements, it LLMs of text-to-render. must significantly improve the quality of And a lot of the solutions that are built its BIM models. for construction today only address the ■ www.augmenta.ai programmatically make sense of that site.

We’ve done a pretty good job of that but there are still specific things that need to be defined like firewalls, as we shouldn’t be cutting through them.

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The new world of Gen AI: are you risk-managed ready?

D

o you remember the days before iPhones? How about Google? Generation-defining tech like this has a way of becoming so pervasive we can barely remember a time ‘before’. Whilst Gen AI tools like Copilot and ChatGPT are relatively new in the general consciousness, their take-up is at a pace rarely seen before. (ChatGPT reportedly hit 100m users in Jan 2022). How long will it be until they form part of our common lexicon as has “to Google”?

As a human race, we are predisposed to be suspicious of the unknown; this caution kept our ancestors alive.

However, in the modern world it often manifests as tech-phobia - a reluctance towards innovation that changes the game a little too much.

I’m sure readers of this article would have seen multiple headlines about how AI is going to come and take over the world.

Those of my generation will remember this idea playing out in the Terminator movies, or more recently in ‘Blade Runner 2049’.

There is no doubt that AI, and related technologies like automation, will change society but anyone who has used the gen AI chatbots will realise that these clunky tools have some generations of development before they equal human intellect, reaching the realms of “general intelligence” AI. It reminds me of being about six years old (many, many years ago!), playing with a purported “intelligent” chatbot on a DOS system in the days pre-Windows. It was exciting at first, but after a few questions I realised the bot required precisely worded questions to avoid repetitive answers. The technology has developed in leaps and bounds in the decades since, but gen AI currently still needs careful prompts to get the answers you seek. Indeed, prompt engineering is so fundamental to the use of gen AI that 16

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it has quickly been established as a whole new profession.

On the flipside, once adopted we have a habit of then blindly trusting technology.

Almost everyone has input their symptoms into Google, which has confidently declared their common infection to be a life-threatening disease. We rarely question the answer given by a calculator to a complicated maths equation, or a translation sought on the internet. Yet nothing is perfect, not even technology and certainly not AI. Most people will be aware that gen AI can “hallucinate”, or in simple terms, make stuff up, if it doesn’t know the answer or wants to provide a more comprehensive one. A lawyer in the US found this out at his peril when gen AI confidently gave him details of a number of cases to support his legal arguments, only for the judge to point out that all these cases were completely fictional (www.tinyurl.com/AI-lawyer). Apparently, it simply had not occurred to him to check.

Many of the kinks in gen AI will be ironed out as the technology develops at its relentless pace. In the meantime, most companies are already embracing the use of gen AI, though in varying degrees and with different levels of understanding.

There are some key risks to bear in mind when implementing gen AI. These risks are likely to remain largely unchanged for the foreseeable future at least - until gen AI technology develops well beyond its current iterations.

These risks can be categorised into a couple of broad categories which I’ll consider briefly below.

Accuracy and reliance As we’ve seen, gen AI can make things up or provide partly inaccurate results.

Imagine asking a gen AI tool if a connection is safe and it gets it wrong; the conse-

quences could be serious. Yet it is not a legitimate defence to assert the gen AI tool itself is at fault. That would be like blaming the calculator for your mathematical errors, or the teacher for the poor quality of your homework.

Ultimately gen AI tools are exactly that, tools to supplement and augment what we do rather than replace it. To blindly rely on gen AI is a folly and fraught with risk. It will be very interesting to also see if courts, and insurers, will regard such actions as knowingly reckless, rather than negligent, and therefore falling outside the protection of professional indemnity insurance.

Confidentiality Readers may have heard the saying, data is the new gold. Project and company data can have great value; knowing how your competitor is pricing or designing their projects could open up a significant competitive edge.

It is tempting to input data into a gen AI tool and ask it to, say, reformat it or provide similar examples. However, inputting data into a public generative AI like ChatGPT is in essence like throwing this data into a public forum. It is not possible to delete or remove it. Someone asking the right question could extract that data, and I have seen some terrifying examples online of people doing exactly that.

Whilst it may not matter for some generic data entry, it has a bigger and serious impact for sensitive client or project data. There was a widely reported example of employees of a major technology company inputting code into ChatGPT for it to fix it, thereby losing control of this code. Such actions could expose your company data to external parties, and as regards client and project data, likely put you in breach of your contractual obligations. I also doubt cliwww.AECmag.com/AI

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Technology is advancing at an ever-faster rate. The buzz around AI is quickly manifesting itself in all the devices and applications that we use in our jobs. How accurate, reliable is the information we get back and how confidential is the data we send? And what about copyright? May Winfield, global director of commercial, legal and digital risks at engineering consultancy Buro Happold shares her insight

ents, and management, would be too pleased at this loss of confidentiality.

It is therefore important to always check the user terms of any gen AI tools before implementing it within your organisation. Can the data be used to train the models? Will the data be accessible to other parties? Where is the data stored? These are just some of the questions to consider in such situations.

Copyright There have been various reports of court cases by newspapers, authors and artists alleging breach of copyright as gen AI tools have scraped data off the internet and/or been fed material in training the models without appropriate copyright licences. Whilst some gen AI companies have entered into copyright agreements with key information providers, there remains a risk that the gen AI output you receive could be partly or wholly in breach of copyright. You simply can’t know until a party alleges such a breach on seeing your output. It is worth therefore thinking cautiously before using gen AI outputs in a public forum, at least insofar as it has not been purely trained on data you own or have rights to use.

A number of software providers are offering indemnities (sometimes for an additional fee) to protect users from claims of copyright breaches in using their gen AI tools. Whilst a responsible step by such organisations, it is recommended to read the wording of such indemnities before paying extra for them, or seeking to rely on them, as some can be quite narrow and have a number of potential loopholes. The jury is also out on how a court would interpret such indemnities in practice.

the GDPR, in the UK and Europe. Such legislation seeks to protect personal data and has a direct impact on how personal data can be input into gen AI tools, particularly public ones.

As regards ethics, it is a known phenomenon that gen AI can be biased, simply because it is trained in historical data that is known to have such bias. A friend working in HR noted that when a gen AI tool was asked to propose the best CVs for a role, all the candidates put forward were white males. As with all risks arising from gen AI, this doesn’t mean you need to turn your back on the technology, simply that you need to put in place risk management and protective measures to counter this known issue.

Conclusion The above is but a flavour of some key issues that should be borne in mind when adopting and implementing this potentially paradigm-shifting new technology.

It’s also important to bear in mind any new AI-specific legislation, most notably the EU AI Act and various US state legislation, and ensure you are in compliance.

We are living in an exciting world of progress, where the possibilities shown in the likes of Bladerunner and Star Trek are increasingly becoming more than a vague possibility. We just need to ensure we have the right safeguards and safety nets to ensure we reap all the potential benefits, whilst avoiding the known pitfalls.

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It is tempting to input data into a gen AI tool and ask it to, say, reformat it or provide similar examples.

However, inputting data into a public generative AI like ChatGPT is in essence like throwing this data into a public forum

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Further reading Chartered Institute of Building (CIOB) AI Handbook: www.ciob.org/industry/research/AI-Playbook

Personal data and ethics

Compilation of my previous A point to note on personal data is the talks and presentations: impact of personal data legislation, like www.maywinfield.squarespace.com www.AECmag.com/AI

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Software

Finch untethered BIM 2.0 is increasingly about forging AI, procedural and parametric rules-based design into new design assistants and automation is coming to most phases of the traditional design process. Architects spend a lot of time designing and revising floorplans. Finch aims to reduce preliminary design time by 80%, as Martyn Day reports

F

inch is an early-stage feasibility code. Meanwhile, the innovation is comtool. It was originally developed ing from start-ups like Finch.

Nunez Wallgren agrees, “It’s exciting by architects as a bespoke inhouse plug in for Rhino to deliv- being in this space right now. It’s been er data-driven massing, storey design, really tough for the big companies to space planning and floor layouts. One innovate. I think that is the strength of thing led to another, and Finch became a being a small startup, with a small agile company, a product and a bit of a legend team - you have a mission, you’re going out to change something, to disrupt somesoon after its initial public showing.

Pamela Nunez Wallgren (CEO) and thing that is difficult to rally around in a big company.”

Jesper Wallgren (CPO) It’s not just software gave a presentation at companies facing difficulAEC Magazine’s NXT The only thing you ty though, AEC firms are DEV 2023 (www.tinyurl. can be sure of also under pressure on com/NXT-Finch).

Finch when you talk to fees and there have been has so far raised $3.1 milseveral layoffs in conlion for development and creative people, as well as insolafter what seemed like a like architects, is struction, vencies. Firms will need lengthy time in stealth, that they don’t to look towards adopting working with a limited number of clients always necessarily productivity tools to become more efficient and (Herzog & de Meuron want to follow a to do more with less. Here and White Arkitekter), straight-line the new generation of has now emerged, ready workflow. Being products like Finch have to expand.

Finch currently sup- able to jump in and a role to play.

“To us, Finch is where ports Rhino, Grasshopper out of the process architects and AI design and Revit, and there is is very crucial to together, and the together an Autodesk Forma link us, but also very part is key to us. We in development. It uses two key underlying techhard when you’re believe that what archinologies, a graph-based really need is a cobuilding a product tects rules engine and an AI pilot, rather than autopiJesper Wallgren learning system for analot.”, explains Nunez lysing and generating Wallgren. “Our waiting optimal floorplans. list has now reached over The software analyses room relation- 80,000 AEC professionals who want to ships - where vertices represent spaces access Finch. We are onboarding more and edges show adjacency - exploring mul- and more leading global architecture tiple iterations by considering concerns firms who want to be part of the develsuch as spatial efficiency and daylight opment but for all of those on the waitoptimisation. Architects can modify these ing list, who are Rhino / Revit users space relationships and requirements working with residential projects, we’re now inviting them to explore Finch and dynamically optimise space usage.

Basic. Finch Basic includes all key figSmall is the new big ures and calculations in this generative As far as AI is concerned, it’s fair to say solution to generate a proper mix and the established AEC software developers circulations, and customers can build have produced more words than useful their own plan library.”

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Finch Basic Finch Basic costs €49 per month and is aimed at those looking to use AI to generate residential designs based on their specified mix, resulting in thousands of iterations meeting the apartment mix and circulation requirements. Users get auto-generated metrics: Gross Floor Area (GFA), Gross Internal Area (GIA), Net Internal Area (NIA), Usable Floor Area (UFA).

There is another tier, Finch Enterprise, aimed at larger firms focussed on residential who have their main workflow in Rhino, but this requires a more manual onboarding process, so is limited by Finch’s in-house resources and cannot be open to everyone.

Enterprise is also built for teams, as opposed to individuals, and will have all the graph rules which have been recently developed, and AI generated plans.

Enterprise customers get to create shared custom plan libraries, furniture libraries, graph rules, and compliance checks.

The main feature in the Enterprise tier is that when generating plans, customers can build their own data sets, to generate results that adhere to local regulations and incorporate their practice’s style (design rules) in their Finch preferences – add custom objects, include accessibility bounds, lock constraints (like corridor / room width). Enterprise customers get two sets of results: one from the custom data set and generic Finch results. (see Enterprise demo video www.tinyurl.com/Finch-D)

Pamela Nunez Wallgren (CEO) (left) and Jesper Wallgren (CPO) (right) www.AECmag.com

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1 Start Point: bring in massing models from Revit Rhino, Grasshopper and start to get immediate feedback before generating floor plates and plans 2 Finch generating a floor plate based on the user’s unit mix, stairwell constraints and weighting, squareness, daylight and area 3 Iterative space plans generated by Finch scored against multiple competing weightings 4 Iterative space plan results: scores against daylight, CO2 efficiency, compliance and adaptivity

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The process Put simply, the architect creates massing in Rhino, Grasshopper or Revit (each mass will be interpreted as a building).

Finch brings in that geometry (via a plugin). If the mass needs to be changed, it can seamlessly bring in those edits from the source conceptual tool.

Finch provides key metrics feedback to the designer: gross floor area and net internal area. It then slices up the building into different storey heights so the process of generating floor plates can happen. This is based on multiple scenarios - unit mix with stairwell variations, double corridors with stairs (US market), or cores connected to corridors (in development). Alternatively, you can generate around an existing corridor / core if you are doing a refurbishment.

The user specifies the number of units to be generated per stairwell.

There are an array of side panel sliders with ‘weights’ which control the bias of the algorithm, daylight, area, grid lines, squareness. As the algorithm works you can see how well the unit mix fits the floor. Finch keeps iterating, and the longer you leave it, the more accurate it will get. This process is amazingly fast. All the time the user has control to impact the space designs which Finch outputs.

Wallgren describes the Finch process as “a dance between generating and editing”, as the architect works with the Finch copilot. Once the floor plate is good, Finch displays all the different variations for unit mix that meet the criteria. Finch Basic can’t produce AI unit plans, so here users can assign a plan from their own library to be applied (watch this video www.tinyurl.com/Finch-AI ).

Those on an Enterprise plan get AI created unit plans, including room load out (furniture etc.) and here Finch takes into account the façade and position of corridors, generating a proper architectural plan drawing, which can be streamed back to either Rhino or Revit, as a native Revit file.

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Improved algorithms As the software develops, the Finch team is constantly tweaking the algorithms and incorporating feedback from customers. The latest version of Generate Floor Plate allows architects to specify a range of stairwells, rather than specifically stating the number, allowing the algorithm to determine the most efficient configuration within these parameters.

This flexibility extends to the distribution of units per stairwell.

Previous iterations of architectural AI tools often operated as black boxes, providing solutions without explaining their methodology. Finch now provides feedback when unit combinations prove incompatible with the building’s defined framework, such as oversized units or excessive stairwell numbers. This immediate feedback removes the need for trial and error.

The previous algorithm would solve within a margin of tolerance, so maybe not all units were exactly the area as specified. The new floorplate algorithm delivers exact dimensional accuracy. The new algorithms now also better cater to spatial constraints for building depth and dual-aspect ratios.

Beyond massing Sometimes a project may already be past the massing stage before Finch gets introduced, as Nunez Wallgren explains, “We have been opening the pipeline allowing users to upload walls from Rhino, Revit, Grasshopper, corridor and the stairwells too, and then just generate the floor plans. We are opening up the 20

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5 Residential plan generated Wallgren is keen to assuage cases where they can use from a floor plate, with walls any customer fears, “One Finch, depending on what and full room load out, seeking thing that we’ve said now stage the design is at.” results on CO2 efficiency - all that has also been very Wallgren adds, “The only powered by Finch’s patented graph technology important to our customers thing you can be sure of is that their plans are not when you talk to creative people, like architects, is that they don’t part of the bigger model that we train. We always necessarily want to follow a collect a lot of data on built projects all straight-line workflow. Being able to jump over the world, to train our models, and in and out of the process is very crucial to then apply this to our customers’ results. us, but also very hard when you’re build- But we’re not training on their data ing a product! The openness and custom- because that has been one hot potato!” isability of the software is key.”

Artificial Intelligence (AI) Finch uses a mixture of techniques to generate and analyse spaces.

“Everything in our system is based on our Finch graph which is the logic of architecture,” explains Wallgren, “When we generate things, Finch doesn’t think it’s a good idea to go from the elevator into the toilet, into the bedroom. It’s more like understanding the composition of space, what makes sense, how we build architecture.

“These kinds of ‘soft’ problems are much more suitable for AI solutions, while, for example, when we generate a floor plate, when you want the core to be 1,400 mm, then a parametric and algorithmic approach is much better. But we are experimenting with other techniques as well.

You can combine techniques, for example, playing chess on a computer. There are algorithms, there are rules, but you could also train the computer to play that game.”

Many firms are worried that AI software developers will steal their IP. With Finch giving design alternatives,

Conclusion

It’s great to see Finch finally getting out a release available for wider adoption, just for firms to see what is possible with algorithmic design in residential space planning. The advanced Enterprise features require a deeper onboarding, and obviously come at a higher cost, so access is limited but still worth talking to Finch about and registering your interest.

It’s interesting that speed really isn’t an issue for Finch; it’s being able to accommodate and understand users’ broad application areas. Finch needs not only deep space planning knowledge but also to be able to cater for an ever-increasing array of design variables. The Floor Plate V2 is a big improvement here and keeping the user updated on what’s happened is so much better than ‘computer says no’.

Finch will be joining us at NXT BLD and NXT DEV in London, 11-12 June 2025, along with all the best AEC software start-ups. Be sure to add the conference to your diary.

■ www.finch3d.com

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ANNA-SEILER-HAUS, INSELSPITAL MAIN BUILDING, BERN UNIVERSITY HOSPITAL, SWITZERLAND ASTOC ARCHITECTS AND PLANNERS, GWJ ARCHITEKTUR, IAAG ARCHITEKTEN ASTOC.DE / GWJ.CH / IAAG.CH PHOTO: © HGESCH

Boost your business with smart design solutions

G R A P H I S O F T. C O M

Technology

Navigating the boom in generative design software Generative Design (GD) tools have become increasingly accessible, empowering architects, engineers, and clients to explore innovative designs and streamline project feasibility. But with so many options, how can AEC professionals choose the right tool to meet their needs?

by Allister Lewis, Automated Data Driven Design (ADDD)

G

enerative Design (GD) is a technology-driven approach to optioneering designs by using algorithms to explore a vast number of possible solutions based on defined constraints and goals.

By inputting parameters such as unit mix, desired building heights, spatial layout requirements, and performance criteria, GD software generates numerous design options. This allows designers to evaluate and select the most optimal solution. Instead of manually crafting each option, designers can review a wide range of solutions, filter and adapt them further, enabling new creativity, or simply getting optimal answers faster for clients.

1. Time to Learn: GD tools have opened the door for many users to explore data driven design but within a proprietary format, without a steep technical learning curve of visual scripting. GD tools still require time and effort to master, which can pose challenges for busy professionals.

range of functionality they offer.

However, no single tool has managed to provide the comprehensive design functionality that meets all user needs. A careful study of requirements is required to make sure the software does what is needed.

A tool for clients and developers

2. Cost: Licensing fees vary from free trials and low introduction fees, to expensive Software as a Service (SaaS) models. When added to the growing list of software required for AEC workflows, this is an additional cost that puts pressure on companies already struggling to manage cash flow. While GD tools may offer long-term savings by accelerating workflows, the recurring monthly costs can deter adoption.

An emerging trend among ConTech software companies is a shift of focus from selling to architects to targeting developers and clients, who may wish to understand site potential before hiring a design team. Tools that automate site analysis and feasibility studies allow them to receive insights into purchases at a much earlier stage. This has The expanding landscape an impact on the architect’s traditional role particularly in the early-stage As the popularity of GD has increased, so design process. has the number of availaThis shift presents ble tools. This is both excitboth opportunities and ing and overwhelming.

GD tools will undoubtedly disrupt early-stage challenges. While it It is clear that GD softmay reduce architects’ ware developers have design within the AEC industry, offering identified early stage feapowerful capabilities that allow users to explore, involvement in early feasibility studies for sibility as an area that GD create, and iterate with unprecedented speed some clients, it also crecan be applied to effectiveates an opportunity ly. The software should for architects to use help designers make decisions faster, using data to confirm project 3. Workflow Integration: Not all GD these tools for clients who seek deeper tools integrate smoothly with existing data insights but prefer not to use the viability, and communicate options more software ecosystems, which can create tools directly. effectively than traditional CAD/BIM friction. Users often rely on a core By accessing data and insights generatauthoring tools. However, this presents a suite of tools, and if a GD solution dis- ed by GD solutions quickly and easily, challenge for professionals to learn which rupts these workflows, it may slow architects could provide value faster, creone is best for them, manage licence costs, productivity. Ensuring compatibility ating more refined designs that align with and then understand how to integrate and ease of integration with a compa- clients’ initial requirements. This them into their own tech stack effectively. ny’s preferred BIM authoring soft- approach suggests architects should Breaking down barriers to adoption ware is crucial for broader adoption. adapt, adopt a solution, and potentially provide new services for clients. GD users Despite the promise of GD, there are still notable barriers to adoption for many 4. Functionality: These tools are new could enhance their role in delivering and are continually expanding the data-driven projects with this approach.

AEC professionals.

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6-12 month tech stack review Test & validate pilot project

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Define project goals Identify target discipline

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10 steps

Apply quantitative 8 evaluation framework

Search on 3 the ADDD marketplace

How to choose the best generative design software for you 7

Consider cost & licence

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Check workflow integration

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Evaluate core features

Assess ease of use

1 Define project goals and requirements ●

6 Check workflow integration and compatibility ●

• Scope: Identify the project type and sector (e.g. residential, commercial, infrastructure)

• Platform integration: Confirm compatibility with core platforms like Revit, Rhino, Archicad, or IFC for seamless BIM integration

• Objectives: Determine what you need the software to accomplish (e.g. optimise layout, enhance sustainability, automate early design stages) • Workstage relevance: Specify the project phase (e.g. concept development, detailed design) for which you’ll use the tool

2 Identify target user disciplines ● • Primary users: Decide if the tool is for architects, engineers, or a developer / client • Interdisciplinary compatibility: Prioritise tools with collaboration features if multiple disciplines are involved, ensuring integration with BIM or CAD platforms for smoother team workflows

3 Search for tools on the ADDD Marketplace ● • Use filters: Search by category, product, or vendor name to narrow down your options

• Data import/export: Ensure the software supports the necessary file types and data exchange formats across your project • Collaborative features: For team-oriented projects, consider tools with real-time collaboration or cloud integration to support smooth communication and data sharing

7 Consider cost and licensing options ● • Budget alignment: Evaluate pricing models (subscription, one-time licence, or payper-use) and align with your project budget • Scalability: Check if the software offers pricing tiers or modular add-ons to accommodate future project needs

8 Apply a quantitative evaluation framework ●

• Explore comparisons: The ADDD Marketplace offers descriptions that highlight each tool’s unique capabilities, helping you to match software to your project’s specific needs

• Quantitative Scoring: Use a framework like the Future AEC Software Specification (FASS) to assess options based on weighted criteria, such as usability, costeffectiveness, and compatibility

4 Evaluate core features and capabilities ●

• Consistency: FASS provides an objective scoring system, ensuring consistency and clarity when comparing multiple software options

• Feature set: List essential features like parametric modelling, AI-driven analysis, or real-time data visualisation • Automation and customisation: Check if the software allows customisable automation for tailored workflows, which can enhance efficiency • Sustainability or compliance: If environmental goals are key, prioritise tools offering lifecycle analysis or sustainable design options

5 Assess ease of use and learning curve ● • Skill level: Assess your team’s technical background to determine if they can quickly learn and adopt the software • Training and support: Look for available training resources, community support, or dedicated help, especially if the software has a steep learning curve

9 Test and validate with a trial or pilot project ● • Trial runs: Opt for software trials or demos, running a small pilot project to evaluate functionality • Team feedback: Collect input from team members to confirm that the software meets project needs, integrates well, and enhances productivity

10 Conduct a 6/12-month tech stack review ● • Scheduled assessment: Set a recurring review of your tech stack every 6 or 12 months to evaluate software performance, relevance, and alignment with evolving project needs • Identify gaps and opportunities: During each review, assess if new tools are needed, if existing ones should be upgraded, or if certain software is no longer effective • Optimise workflow: Ensure all tools remain compatible and continue to support seamless workflows, adjusting as necessary to integrate new solutions that improve efficiency and project outcomes

www.AECmag.com

September / October 2024

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Technology The ADDD Marketplace currently features 35 options for Generative Design

work of questions designed to bring clarity and consistency to software evaluation.

When combined with a qualitative approach, where users can communicate their findings and thoughts, a report can be produced that supports the AEC industry to have a consistent way to assess software.

The assessment provides a structured, objective way to assess GD tools on critical factors such as ‘Designing in Context & Scale’, ‘User Experience’, ‘Modelling Capabilities’, and the other criteria from the FASS. By applying the FASS criteria, users can identify tools that align with their needs, budget, and project demands, allowing them to make decisions that suit their requirements. This approach not only simplifies the selection process but also ensures that chosen tools meet the demands of modern AEC workflows.

I am also advocating for Best For …’ results, rather than one software being better than another, as this is too simplistic. In a landscape flooded with options, having a consistent assessment method like the FASS can be invaluable, helping users to navigate to the appropriate GD tool that is ‘Best For Their Needs’.

N.B Information about the assessment criteria can be found at https://addd.io/ product/fass-criteria. ADDD also welcomes feedback on how software is assessed.

Charting a way forward

Risks and challenges While the potential benefits of GD are clear, there are some risks that users should consider carefully: 1. Quality vs. quantity: The ability to generate a multitude of designs quickly can be both a blessing and a curse.

With too many options, architects may face decision fatigue, or find themselves sacrificing quality for speed.

2. Cost and learning barriers: For many architects, especially smaller firms, the cost and time to learn required to adopt these tools remains a hurdle.

3. Dependence on technology: Overreliance on GD tools can sometimes overlook essential design considerations that come from experience, intuition, and human creativity. Designers who depend heavily on GD software 24

November / December 2024

should augment this with a hands-on design approach that allows for unique, site-specific insights.

How to assess GD tools With the growing variety of GD tools, users need a consistent way to evaluate software that goes beyond features and marketing hype. This is why at ADDD, we have developed an assessment criteria, based on the Future AEC Software Specification (FASS) (www.tinyurl.com/ AEC-FASS).

The aim is to enable a consistent approach to reviewing software so different tools can be compared to each other.

This assessment methodology was presented at AEC Magazine’s NXT DEV conference (see presentation at www.tinyurl. com/NXTDEV-FASS) and has now been used to assess four Clash Detection and Issue Management software.

The outcome is a quantitative frame-

GD tools will undoubtedly disrupt earlystage design within the AEC industry, offering powerful capabilities that allow users to explore, create, and iterate with unprecedented speed. This will require adaptability, a consistent structure to assessing software, and a way to help strategic decision-making within organisations.

As GD options continue to search for their specific niche, AEC professionals have the opportunity to explore and embrace these tools as allies in their work, with the opportunity to lead to better client outcomes. With resources like the FASS Assessment, users can assess, compare, and select the solution that aligns with their organisational goals, empowering them to succeed in a digital future that balances creativity with technology.

■ www.addd.io

Learn more @ NXT DEV At NXT DEV in June Allister Lewis presented ADDD’s assessment methodology based on the Future AEC Software Specification. See the presentation at www.tinyurl.com/NXTDEV-FASS

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Feature

Autodesk charts its AI future

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If 2023 was the year that Autodesk announced its ambitions for AI, 2024 was when it fleshed out some of the details. But, as Greg Corke reports, there’s still a long journey ahead

he Autodesk AI brand debuted in Las Vegas last year at Autodesk University 2023, but the launch lacked any real substance. Despite a flashy logo there were no significant new AI capabilities to back it up. The event seemed more like a signal of Autodesk’s intent to add greater focus on AI in the future — building on its past achievements. It came at a time where ‘AI-anything’ was increasing share valuations of listed companies.

Fast forward 12 months and at Autodesk University 2024 in San Diego the company delivered more clarity on its evolving AI strategy — on stage and behind the scenes in press briefings. Autodesk also introduced a sprinkling of new AI features with many focused on modelling productivity, signalling that progress is being made. However, most of these were for manufacturing with little to excite customers in Architecture, Engineering and Construction (AEC), other than what had already been announced for Forma.

In his keynote, CEO Andrew Anagnost took a cautious tone, warning that it’s still early days for AI despite the growing hype from the broader tech industry.

Anagnost set the scene for the future.

“We’re looking at how you work. We’re finding the bottlenecks. We’re getting the right data flowing to the right places, so that you can see past the hype to where there’s hope, so that you can see productivity rather than promises, so that you can see AI that solves the practical, the simple, and dare I even say, the boring things that get in your way and hold back you and your team’s productivity.”

One of those ‘boring things’ is sketch constraints, which govern a sketch’s shape and geometric properties in parametric 3D CAD software like Autodesk Fusion, which is used for product design and manufacturing.

Fusion’s new AI-powered sketch autoconstrain feature streamlines this process by analysing sketches to detect intended spatial relationships between aspects of the design.

Automatically constraining sketches is just the starting point in Autodesk’s broader vision to use AI to optimise and automate 3D modelling workflows. As

Anagnost indicated, the company is ability to generate drawings. During the exploring how AI models can be taught to AU press conference, CEO Andrew understand deeper elements of 3D models, Anagnost hinted that drawing capabiliincluding features, constraints, and joints.” ties might be in Forma’s future, which, if At AU, no reference was made to simi- realised, could potentally impact how lar modelling productivity tools being much customers rely on Revit as a docudeveloped for Autodesk’s AEC products, mentation tool in the long term.

Both of Autodesk’s new AI-powered including Forma. However, Amy Bunszel, executive VP, AEC at Autodesk, features are designed to automate comtold AEC Magazine that the AEC team plex, repetitive, and error-prone processes, significantly reducing the time that will learn from what happens in Fusion.

Another ‘boring’ task ripe for automa- skilled designers spend on manual tasks. tion is the production of drawings. This This allows them to focus on more critilabour-intensive process is currently a cal, high-value activities. But, as hot topic in CAD (read this AEC Magazine Anagnost explained, Autodesk is also exploring how AI can be used to fundaarticle - www.tinyurl.com/AEC-drawing).

This capability is also coming first to mentally change the way people work.

One approach is to enhance the creaAutodesk’s product design and manufacturing product. With Drawing tive process and Form Explorer is a new Automation for Fusion, Autodesk is automotive-focused generative AI tool using AI to automate the process, down for Autodesk Alias, designed to bridge the gap between 2D ideation and tradito the precise placement of annotations.

With the click of a button, the AI exam- tional 3D design. It learns from a compaines 3D models and does the time-con- ny’s historical 3D designs, then applies suming work of generating the 2D draw- that unique styling language.

Lessons learned from Form Explorer ings and dimensions required to manuare also helping Autodesk augment and facture parts. The technology has evolved since its initial accelerate creativity in other areas of release earlier this year and conceptual design. now accelerates and streamProject Bernini is an experimental lines this process even more proof-of-concept research project that by laying out drawing uses generative AI to quickly genersheets for each component ate 3D models from a variety of inputs in a model and applying a including a single 2D image, multistyle. Early next year, the ple images showing different views of an object, point technology will be able to clouds, voxels, and text. The recognise standard generated models are components like fasdesigned to be ‘functionalteners, remove them ly correct’, so a pitcher, for from drawing sets, example, will be empty and automatically add inside. As the emphasis is them to the bill of mateon the geometry, Bernini rials for purchase. does not apply colours and Once again, this featextures to the model. ture will first appear in Project Bernini is not Fusion, but sources have designed to replace manual confirmed plans to extend 3D modelling. “Bernini is automated drawing capabilithe thing that helps you get ties to Revit—a significant to that first stage really development given the BIM quickly,” said Mike Haley, tool’s widespread use for docsenior VP of research at umentation.

There’s also potential for autonomous Autodesk. “Nobody likes the Autodesk CEO drawings in Forma, although blank canvas.”

Andrew Forma would first need the Project Bernini is industry Anagnost

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agnostic and is being used to explore practical applications for manufacturing, AEC and media and entertainment. At AU the emphasis was on manufacturing, however, where one of the ultimate aims is to learn how to produce precise geometry that can be converted into editable geometry in Fusion.

However, there’s a long way to go before this is a practical reality. There is currently no established workflow, plus Bernini has been trained on a limited set of licensed public data that cannot be used commercially.

AI for AEC Autodesk is also working on several AI technologies specific to AEC. Nicolas Mangon, VP, AEC industry strategy at Autodesk, gave a brief glimpse of an outcome-based BIM research project which he described as Project Bernini for AECO. He showed how AI could be used to help design buildings made from panellised wood systems, by training it on past BIM projects stored in Autodesk Docs. “[It] will leverage knowledge graphs to build a dataset of patterns of relationship between compatible building components, which we then use to develop an auto complete system that predicts new component configurations based on what it learned from past projects,” he said.

Mangon showed how the system suggests multiple options to complete the model driven by outcomes such as construction costs, fabrication time and carbon footprint. This, he said, ensures that when the system proposes the best options, the results are not only constructible, but also align with sustainability, time and cost targets.

Another AEC focused AI tool, currently in beta, is Embodied Carbon Analysis in Autodesk Forma, which is designed to www.AECmag.com

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give rapid site-specific environmental design insights. “It lets you quickly see the embodied carbon impact at the earliest conceptual design phase, giving you the power to make changes when the cost is low,” said Bunszel.

The software uses EHDD’s C.Scale API which applies machine learning models based on real data from thousands of buildings. The technology helps designers balance trade-offs between embodied carbon, sun access, sellable area, and outdoor comfort etc.

Embodied Carbon Analysis in Autodesk Forma follows other AI-powered features within the software.

With ‘Rapid Noise Analysis’ and ‘Rapid Wind Analysis’, for example, Forma uses machine learning to predict ground noise and wind conditions in real time.

Autodesk AI is also providing insights in hydraulic modelling through Autodesk InfoDrainage, as Bunszel explained, “You can place a pond or swale on your site and quickly see the impact on overland flows and the surrounding flood map.”

Simple AI Autodesk is also diving into the world of general purpose AI through the application of Large Language Models (LLMs).

With Autodesk Assistant, customers can use natural language to ask questions about products and workflows.

Autodesk Assistant has been available on Autodesk’s website for some time and is now being rolled out gradually inside Autodesk products.

“The important thing about the system, is it’s going to be context-aware, so it’s understanding what you’re working on, what project you’re on, what data you’ve run, maybe what you’ve done before, where you are within your project, that kind of thing,” said Haley.

With the beta release of Autodesk Assistant in Autodesk Construction Cloud, for example, users can explore their specification documents through natural language queries, as Bunszel explained, “You can ask the assistant using normal everyday language to answer questions, generate lists or create project updates,” she said, adding that it gives you access to intuitive details from your specifications that usually require lots of clicking or page turning or highlighting to find.

Getting connected Like most software developers Autodesk is harnessing the power of LLMs or vision models, such as ChatGPT and Gemini. “We can use them, we can adapt them, we can fine tune them to our customers’ data and workflows,” said Haley, citing the example of Autodesk Assistant.

But, as Haley explained, language and vision models don’t have any sense of the physical world, so Autodesk is focusing much of its research on developing a family of foundation models that will eventually deliver CAD geometry with ‘high accuracy and precision’.

Autodesk’s foundation models are being trained to understand geometry, shape, form, materials, as well as how things are coupled together and how things are assembled.

“Then you also get into the physical reasoning,” added Haley. “How does something behave? How does it move? What’s the mechanics of it? How does a fluid flow over the surface? What’s the electromechanical properties of something?”

According to Anagnost, the ultimate goal for Autodesk is to get all these foundation models talking together, but until this happens, you can’t change the paradigm.

“Bernini will understand the sketch to create the initial geometry, but another November / December 2024

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model might understand how to turn sketch auto-constrain or automated that geometry into a 3D model that actu- drawings, “No one has intellectual propally can be evolved and changed in the erty on how to constrain a sketch,” said future,” he said. “One might bring model- Anagnost. “[For] that we just train away.”

This point was echoed by Hooper in relaling intelligence to the table, one might bring shape intelligence to the table, and tion to automated drawings, “Leveraging one might be sketch driven, the other one information that we have in Fusion about how people actually annotate drawings is might be sketch aware.” not leveraging people’s core To provide some context IP,” he said. for AEC, Autodesk CTO Raji To help bring more transArasu said, “In the future, Autodesk’s parency to how Autodesk is these models can even help long-term plan using customer data for you generate multiple levels training its AI models, of detail of a building.” is to get Autodesk has created a multiple AI model training series of Autodesk AI foundation transparency cards which Model training is a fundamodels to talk will be made available for mental part of AI, and each new AI feature. “These Anagnost made the point that together, but labels will provide you a data must be separated from this doesn’t clear overview of how each methods, “You have to teach mean we are AI feature is built, the data the computer to speak a certhat is being used, and the heading for tain language,” he said. benefits that the feature “We’re creating training true design offers,” said Arasu. methods that understand 3D automation Of course, some firms will geometry in a deep way. any time soon not want to share their data Those training methods are under any circumstances. data independent.”

Anagnost believes that this With Project Bernini Autodesk is licensing public data to essen- may lead to a bifurcated business model tially create a prototype for the future. “We with customers, where Autodesk builds use the licence data to show people what’s some foundational intelligence into its models and then licenses them to individupossible,” said Anagnost.

For Bernini, Autodesk claims to have al customers so they can be fine-tuned with used the largest set of 3D training data private data. ever assembled, comprising 10 million examples, but the generated forms that AI compute were demonstrated — a vase, a chair, a AI requires substantial processing power spoon, a shoe, and a pair of glasses — were to function efficiently, particularly when still primitive. As Tonya Custis, senior it comes to training. With Autodesk AI, director AI Research, admitted there sim- everything is currently being done in the ply isn’t enough 3D data anywhere to cloud. This can be expensive but, as build the scale of model required, high- Anagnost boasted: “We have negotiating lighting that the really good large lan- power with AWS that no customer guage and image models are trained on would have with AWS.” the entire internet.

Relying on the cloud means that in “It’s very hard to get data at scale that order to use features in Fusion like auto very explicitly ties inputs to outputs,” constraints or drawing automation, you she said. “If you have a billion cat pic- must be connected to the Internet. tures on the internet that’s pretty easy to This might not be the case forever, get that data.” however. Arasu told AEC Magazine that The billion-dollar question is where will AI inferencing [the process of using a Autodesk get its training data from? At trained AI model to make predictions or AU last year, several customers expressed decisions based on new data] could go concern about how their data might be local. She noted some of Autodesk’s cusused by Autodesk for AI training. tomers have powerful workstations on This was a hot topic again this year their desktops, implying that by using and in the press conference Anagnost the cloud for compute would mean a provided more clarity. He told journal- waste of their own resources. ists that for a generative AI technology like Bernini, where there’s a real possibil- All about the data ity it could impact on intellectual proper- It goes without saying that data is a critical ty, customers will need to opt in. component of Autodesk’s AI strategy, parBut that’s not the case for so-called ticularly when it comes to what Autodesk ‘classic productivity’ AI features like calls outcome-based BIM, as Mangon

‘‘

’’

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November / December 2024

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explained, “Making your data from our existing products available to the Forma Industry Cloud will create a rich data model that powers an AI-driven approach centred on project outcomes, so you can optimise decisions about sustainability, cost, construction time and even asset performance at the forefront of the project.”

To fully participate in Autodesk’s AI future, customers will need to get their data into the cloud-based common data environment, Autodesk Docs, which some customers are reluctant to do, for fear of being locked in with limited data access only through APIs. Autodesk Docs can be used to manage data from AutoCAD, Revit, Tandem, Civil 3D, Autodesk Workshop XR, with upcoming support for Forma. It also integrates with third-party applications including Rhino, Grasshopper, Microsoft Power BI and soon Tekla Structures.

The starting point for all of this is files but, over time, with the Autodesk AEC Data Model API, some of this data will become granular. The AEC Data Model API enables the break-up of monolithic files, such as Revit RVT and AutoCAD DWG, into ‘granular object data’ that can be managed at a sub-file level.

“With the AEC Data Model API, you can glimpse into the future where data is not just an output, but a resource,” said Sasha Crotty, Sr. Director, AEC Data, Autodesk. “We are taking the information embedded in your Revit models and making it more accessible, empowering you to extract precisely the data you need without having to dive back into the model each time you need it.”

Crotty gave the example of US firm

AI Transparency Card

1

Autodesk Research

Project Bernini Research

Description

The model generates functional 3D shapes from a variety of inputs including 2D images, text, xels, and point clouds.

Feature information Feature functionality

Aunment

Model source Primary techni ue

Proprietary Transformer Diffusion

Trust in¡redients User directed feature

Yes

Personal data

No

Data source(s)

Open-source

Choice format

NÞA

Encryption at-rest

NÞA esearch onîyô

Encryption in-transit

NÞA esearch onîyô

Other safeguards

NÞA esearch onîyô

For more information on our Trus consult our Trust Center.

AI practices,

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Feature 1 To help build trust in AI, Autodesk AI Transparency Cards are designed to explain how each AI feature is built, the data used, and the benefits it offers

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2 AutoConstrain in Fusion Automated Sketching helps maintain a designer’s intent throughout project iterations by detecting and suggesting dimensional constraints between aspects of a design 3 In Fusion, AI automates the time-consuming process of creating 2D drawings from 3D models

Avixi, which is using the API to extract Revit data and gain valuable insights through Power BI dashboards.

When the AEC Data Model API launched in June, it allowed the querying of key element properties from Revit RVT files. Autodesk is now starting to granularise the geometry, and at AU it announced it was making Revit geometric data available in a new private beta.

For more on the AEC Data Model API read this AEC Magazine article - www. tinyurl.com/Datamodel-AEC. Autodesk Docs is also being used to feed data into Forma Board, a digital whiteboard and collaboration tool that allows project stakeholders to present and discuss concepts.

“Forma Board lets you pull in visuals from Forma and other Autodesk products through Docs, and now you can demonstrate the impact of sun or noise, ask for feedback on specific concepts, and much more,” said Bunszel.

Revit also got some airtime, but the news was a little underwhelming.

Bunszel shared her favourite Revit 2025 update – the ability to export to PDF in the background without stopping your work. Meanwhile, manufacturing customers were being shown the future, with new features coming to Inventor 2026 such as associative assembly mirror and part simplification.

In the press conference Anagnost reiterated how Forma is different to Revit.

“It is driven by outcomes,” he said. “We not trying to redo Revit in the cloud.”

Anagnost added that Forma is going to start moving downstream into things that Revit ‘classically does well. “It doesn’t mean it has to swallow all of Revit, and you know that would take a long time, but it can certainly do things that that Revit does today as it expands,” he said.

An iterative future Autodesk is beginning to add clarity to its AI strategy. It is addressing AI from two angles: bottom up, bringing automation to repetitive and error prone tasks, and top down with technologies like Project Bernini that in the future could fundamentally change the way designers and engineers work. The two will evenwww.AECmag.com

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3

tually meet in the middle.

Autodesk is keen to use AI to deliver practical solutions and the automation of drawings and constraints in Fusion should deliver real value to many firms right now, freeing up skilled engineers at a time when they are in short supply.

We expect automated drawings will find their way into Autodesk AEC products soon, but it’s hard to tell if Autodesk has any concrete plans to use AI for modelling productivity.

As to pushing data into Autodesk Docs to get the maximum benefit out of AI, the fear that some customers have of getting trapped in the cloud is unlikely to go away any time soon.

Meanwhile, it’s clear there’s still a long way to go before the AI foundation models being explored in Project Bernini can deliver CAD geometry with ‘high accuracy and precision’.

While Bernini is starting to understand how to create basic geometry, the 3D models need more detail, and Autodesk must also work out how they can be of practical use inside CAD. With rapid advances in text-to-image AI, one also wonders what additional value text-to-CAD might bring

to concept design. One could also ask whether product designers, architects or engineers would even want to use something like this to kickstart their design process. As the technology is still so embryonic it’s very hard to tell. It’s also important to remember that Bernini is a proof-of-concept, designed to explore what’s possible, rather than a practical application.

Meanwhile, as Autodesk continues to develop the complex AI training methods, there’s also the challenge of sourcing data for training. It will be interesting to see how Autodesk’s trust relationship with customers plays out.

While Autodesk’s long-term plan is to get multiple foundation models to talk together, this doesn’t mean we are heading for true design automation any time soon.

At AU Anagnost admitted that the day where AI can automatically deliver final outcomes from an initial specification is further away than one might think. “For those of you who are trying to produce an epic work of literature with ChatGPT, you know you have to do it iteratively,” he said.

That same iterative process will apply to AI for design for some time to come.

■ www.autodesk.com

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Feature

Graphisoft accelerates development Graphisoft recently hosted its annual product release at its HQ, next to the Danube in Budapest. With a new CEO, an ever-broadening multidisciplinary product suite and a drive to subscription, Martyn Day found a company focussed on extending its global footprint

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raphisoft is part of the Nemetschek Group, which comprises thirteen AEC related brands, three of which are BIM modellers. While the brands are individually strong, it’s taken a while for Nemetschek to realise that together they can represent a connected ecosystem solution for the whole AEC industry. This has resulted in a change of strategy, with growing interconnected workflows and now brand separated teams working together on company-wide technology innovation.

Graphisoft, which has Archicad as its flagship BIM platform, is set to become a major beneficiary of Nemetschek’s new pan-brand accelerated development.

In 2023, Graphisoft took a significant step forward by beginning to circulate comprehensive product roadmaps for Archicad, BIMcloud, BIMx, and DDScad (MEP – mechanical, electrical, plumbing).

These roadmaps categorised the status of various features as ‘under research’, ‘in progress’, ‘coming soon’, and ‘delivered’.

Graphisoft also introduced a Technology Preview Program, to share and experiment with forthcoming features, so users

can have input on the development and evolution of Archicad.

This year, we were invited to play with a range of augmented reality (AR) and artificial intelligence (AI) technologies that are still in the experimental phase, sparking discussions about the transformative potential of AI within the AEC sector.

The transition to a subscription model has evidently fostered a more open dialogue from Graphisoft’s product managers, who now appear more inclined to speculate on the future trajectory and capabilities of BIM 2.0, as well as the broader applications of technology across the AEC market.

This is indeed an opportune moment for AEC technology developers, as the landscape is ripe with possibilities for the creation of innovative solutions. The shift towards a subscription model potentially enhances customer engagement, and also allows for a more agile response to market demands and technological advancements. As Graphisoft continues to evolve and adapt to the changing dynamics of the industry, the potential for collaboration and integration among the various

Nemetschek brands will likely yield significant benefits for architects and other professionals within the AEC sector.

The strategic realignment within the Nemetschek group, coupled with Graphisoft’s newfound transparency regarding its product roadmap, heralds an exciting chapter for the company.

Graphisoft is fostering a future where technology not only enhances customer’s design capabilities but also fosters a more interconnected and collaborative approach to building and construction.

The journey ahead promises to be filled with opportunities for growth, innovation, and the advancement of our profession.

Graphisoft 2024 lineup Graphisoft’s core product, Archicad, is now in its 28th revision. For an opener, this year’s update offers a substantial 30% improvement in performance and the development team is impressed with Apple’s new ‘system on a chip’ siliconbased systems. Asked if Graphisoft would support the ARM version of Windows, it seemed the company had the software compilers and were working towards

Archicad Collaborate In March 2023, Graphisoft offered the Archicad Collaborate subscriptionbased, value bundle for power users. This combined Archicad, BIMcloud as a service, Graphisoft Learn courses and materials, Redshift renderer by Maxon, PARAM-O object design tool, Library Part Maker and Python API for a single discount subscription fee.

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The 2024 Collaborate offering is intended to replace its Software Service Agreement (SSA) / Forward (FWD) subscription program, and includes Archicad, BIMx Pro, BIMx model transfers (private storage, password protection, embedding), Redshift, Surface Catalogue (500+), Python API, PARAM-O, Library Part Maker,

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Technical support, Graphisoft Learn, Emergency licences (replace lost or stolen keys), and Archicad Design Checker (powered by Solibri).

Collaborate is essentially the full Graphisoft tech stack and enables centralised project management with real time synchronisation across all connected devices and team members. There’s built in version control, logging

and tracking all iterations, and there are quality checking and conflict resolution tools. Designs can be shared with team members and clients, sent for markup and annotation. Tasks can be assigned and tracked. Access is controlled based on roles.

BIM data is stored securely in the cloud and distributed across multiple platforms.

The cloud server provides

automatic back-up and utilises the power of the cloud, freeing up local machines for other tasks.

From 2026 Archicad will be available for purchase only via subscription. The bundle options appear to be Archicad Collaborate now or Archicad Studio in 2025. We suspect the individual products will remain as subscription items on the menu.

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Archicad’s new Design Options allows users to create variations of a building within a single file

There’s a new LCA (Life Cycle sections, and elevations. It’s possible to future support for Archicad on ARM. There are the usual UI tweaks, like a merge, duplicate, or rearrange options Assessment) analysis capability provided new home page start point on launch. within the workflow. This is a very pow- by third party developer One Click, to Improved model exchange support erful technique, and one that is used in give fast feedback on lifecycle assessthrough IFC, RFA and RVT for Revit. the more advanced mechanical CAD ments and life cycle costing of their variNew support for Information Delivery tools. It reduces the need to start multiple ous design options.

Point cloud has been improved with the Specification (IDS) format - a protocol for project files to develop different options.

Archicad has improved Rhino- inclusion of a ‘Lite’ layer of functionality enabling the construction sector to establish and validate BIM specifications, Grasshopper connection which supports from third-party developer, BIMmTool, leading to the automation of quality the latest version of Rhino. It offers aimed at assisting renovation and refurassurance checks and categorisation. increased speed with a built-in paramet- bishment projects within Archicad. It Graphisoft has also added support for ric hotlink capability, where Archicad means Archicad can now handle larger geometry becomes hotlinks in data sets, leading to faster workflow. To BIM Collaboration Format (BCF) 3.0.

Advanced distance arrows / guides Grasshopper – enabling capabilities such maintain speed while handling dense give excellent measurement feedback as laying out of buildings. Beam and col- point clouds, the software displays distant point clouds at lower resolution. when moving and positioning to relative umn support has also been extended.

Users that want even more power can The Archicad AI Visualizer, which geometry. Roof openings can be created upgrade to the full version quicker and more confrom BIMmTool, which sistently in an expanded supports the direct import Opening Tool. There’s a Customers want to buy into a technology firm that of common point cloud flexible global library, has a vision and can show velocity of innovation. formats, such as Leica, ‘Keynotes’ debut in Archicad 28, to enable a BIM software needs to deliver considerably more Faro, Riegl and others.

Thanks to multiprocessdatabase-driven docuproductivity to users and I don’t get the feeling ing support and sampling, mentation system that Graphisoft is resting on its laurels BIMmTool supports large integrates specifications scan projects easily, while and legends. This is the Pointcloud switcher streamlined by automating annotations, eliminating the manual was originally desktop-based, now runs allows precise control over point cloud workarounds that were previously in the cloud, which means it doesn’t have display in Archicad views. The full verrequired for maintaining consistency to be installed, and users don’t need pow- sion also provides a suite of tools for moderful local GPUs. The software takes elling off point clouds, as well as analysis across project documentation sets.

Architects face a common challenge Archicad designs and uses AI to generate for deviation of reality vs BIM. Archicad also offers improved integrawhen presenting multiple design con- photorealistic images based on text cepts to clients. The process typically prompts. To change a material, the user tion with its sister Nemetschek brands, requires many hours to manually create simply alters the text prompt and the including Solibri for design checking / validation and Bluebeam for PDF-based different versions of the same project. image is regenerated.

Graphisoft still has strong links with collaboration.

Archicad’s new Design Options delivers a new workflow within a single project Chaos Group and its Enscape renderer too file. Users can create variations for a for more traditional viz output. The new DDScad for MEP whole building or focus just on specific Chaos AI Enhancer is also accessible to In June 2022, Graphisoft merged with its areas. Different façade treatments or Archicad users, delivering exceptionally sister company, DDScad, adding the MEP interior layouts are good examples. smooth daylight shadows. In fact, there expertise of DDS to its BIM platform. This These alternatives work independently, are no shortages of rendering tech, as there was a major step forward to producing a allowing for smooth 2D and 3D views is also Graphisoft’s stablemate, Maxon, like for like multi-disciplinary BIM sysand are compatible with annotations, which offers Redshift and Cinema 4D too. tem to compete with Revit. Unfortunately,

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the Archicad brand obfuscates the fact that the BIM tool is more than just about architecture. It now offers MEP, as well as structural, through other Nemetschek brands. The integration work is significant and Graphisoft maintains DDScad as a standalone product for its significant European installed base.

DDScad is an advanced MEP solution which designs ductwork specifications with flow rate optimisation, with an easy-to-use browser-based system to visualise routes. It also delivers streamlined cable tray and piping workflows and real-time size optimisation, based on flow requirements.

New for this year, there are enhancements to photovoltaic system design, busbar trunking design and modelling and generic workflow improvements, specifically allowing electrical engineers and architects to exchange models easily.

Lighting design also gets updated with an improved DIAlux-evo electrical connection, for planning, calculation and visualisation of lighting. Dial is the company which develops DIAlux-evo in Germany and is available free in 26 languages.

BIMcloud for collaboration Graphisoft’s cloud-based data platform, BIMcloud, for architects, engineers, and

constructors enables real-time collaboration on projects. BIMcloud has 13 regional data centres worldwide through Graphisoft’s partnership with Google Cloud Platform.

While BIMcloud was slow to gain adoption, like all cloud collaboration tools it has started to get traction post COVID, with remote working and distributed teams growing and fears of cloud subsiding. This year, multi-factor authentication is being added to build in more security and Graphisoft is offering it as a turnkey service.

BIMx for presentations Graphisoft’s collaboration and presentation tool, BIMx, now supports antialiasing, leading to better quality model edge definition. The new release also provides feature unification across all supported platforms, mobile, web and desktop macOS, Safari, Windows, Firefox, iOS, Android, Chrome and others.

There are more controls to filter visibility options to enable the viewing of design options, renovations and structure. This is easy to use and an incredibly effective visual aid when showing clients.

BIMx now supports the Apple Vision Pro, although since the announcement Apple has paused production of the high-

resolution headset, and rumours are that work on the second generation has been suspended. We hope this work progresses once Apple figures out the way ahead.

Autodesk Nemetschek API deal In April this year, Nemetschek and Autodesk signed an agreement to advance and open interoperable workflows between their products. This was great news and included the exchange of software, API developer access and for Nemetschek to access Autodesk Platform Services APS (formerly Forge). This lowered the bar of entry for Nemetschek to connect Bluebeam, BIMcloud and BIMplus to Autodesk Forma, Autodesk Fusion, Autodesk Construction Cloud (ACC) and design products.

While it’s still early days, it was interesting to discuss the opportunities this might present to Graphisoft. It’s possible that Graphisoft could develop tools that rely on APS, which essentially is Autodesk’s modularised services, like viewing tools, file translation, design automation, and even access to the new granular data and geometry feeds from Autodesk Docs, which were launched this year.

Co-opetition is a strange new world as AEC firms open up, but it was encouraging to hear that Graphisoft’s team were

AI / ML and legacy code In a CAD world full of artificial intelligence (AI) and machine learning (ML), it will be obvious to see that there is not a lot of innovative AI shipping with Archicad currently.

The most notable component was this year’s inclusion of the AI Visualiser tool, but this was released in a world of exploding AI visualisation tools, which basically all do the same thing - harness ChatGPT with and AI renderer (Stable Diffusion), using BIM geometry as the seed. EvolveLab was first to market with Veras in 2022.

AI Visualiser was a rapidly developed tool, which started off as an in-house AI experiment that progressed rapidly and gave impressive results so the decision was made to release it.

I talked with Màrton Kiss, Graphisoft CPO and Sylwester Pawluk, senior

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director of product management about AI, preArchicad 28 launch, back in September 2024 (www.tinyurl. com/Gsoft-AI). At the event we had plenty more time to further our conversations and talk about the future application of AI. Both Nemetschek and its brands are all active in developing AI features and new products and this is being managed centrally by an AI group at Nemetschek.

We will see discreet AI applied within Nemetschek’s brands, jointly developed technology between different brand developers and possibly new products emerge in their own right from Nemetschek.

The Graphisoft product team is certainly not short on ideas. Our conversations ranged from automated detail modelling, 2D to 3D BIM, 3D BIM to 2D drawings, mass transcription of architectural

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catalogues to 3D BIM components, scan a room direct to AR, auto routing of MEP, auto modelling of MEP, automatic structural design based on architectural BIM modelling, modelling with intelligent massing rooms which automatically generate Level 300 detail models.

All of these topics are being considered or are in some form of being actively researched.

Depending on how well they go, they could end up on the Archicad roadmap or be taken up within the Nemetschek Group as they could benefit all brands.

It is of course possible that the AI technology is deemed so game changing that it is kept in stealth until unleashed. With the industry seeing so many cloud-based ‘wannaBIM’ start-ups and the future battle for the AEC design authoring tool for the next decade.

Talking with Pawluk, who

Archicad AI Visualizer

was previously at GE Healthcare / GE Avionics and Google, you can’t help but get excited about the potential applications for AI within the whole product suite. But with this new change of pace in development, it’s important not to break the existing product and still deliver reliable code.

We know internally the company has engaged in a multi-year project to rewrite and modernise Archicad’s core underlying code, removing the legacy. Called

the Adaptive-Hybrid Framework (AHF), that program is being led by Zsolt Kerecsen, Graphisoft’s CTO (www.tinyurl.com/AEC-AHF).

Essentially Archicad’s core has to become modular, extensible, support cloud and desktop as native, and be ready to deliver quarterly feature updates and AI, ML / neural net-based capabilities.

In fact, some of this work has already been done as two of this year’s features utilised the AHF - Design Options and Keynotes.

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Feature aiming to make use of this agreement in building connected AEC workflows, trying to remove the historic silos.

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Conclusion It’s incredible how broad the Graphisoft software and services portfolio has grown - now catering to architects, electrical engineers, mechanical engineers, sustainability experts, construction specialists, and arch viz experts, extending out to surveyors, and then customers with BIMx. With each release, the span of software development grows.

This release also sees Graphisoft do something else it has not been so good at in the past - working with third parties.

Bringing in BIMmTool and One Click LCA, this enables ‘lite’ layers of functionality to be integrated, exposing their customers to third party tools which build on the functionality provided, adding extra levels and layers to Archicad’s capabilities.

Graphisoft will convert to selling only new subscription licences from 2026 which is a sure-fire way to rile up the base as inevitably the cost of ownership goes up. This can be assuaged to a degree by offering more value and much longer lowcost subscription deals. The messy bit with subscription is time and price inflation compound inflation eventually adds up to make an expensive solution and software providers fall foul with even their in-house product champions. However, maybe in ten years, AI will mean that eventual seat sales of software may have to make way for a new value-based pricing model.

It’s interesting how attitudes are changing in the software development community. While I am not a massive fan of subscription for many reasons, there is one positive thing that is coming from it and that is open product development. It’s no longer about selling the next release and trying to get as much of the base to buy in to this year’s features. We have moved decisively to open development, where customers get a much longer view of where software development teams have been going.

Customers want to buy into a technology firm that has a vision and can show velocity of innovation. BIM software needs to deliver considerably more productivity to users and for the first time in 20 plus years there are some new kids on the block. I don’t get the feeling Graphisoft is resting on its laurels, and that sentiment now spans the whole Nemetschek Group.

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1 DDScad, Graphisoft’s MEP solution, features several improvements that allow electrical engineers and architects to exchange models easily 2 Archicad has improved support for point clouds thanks to a ‘Lite’ layer of functionality from thirdparty developer, BIMmTool, aimed at assisting renovation and refurbishment projects

3 Archicad has improved collaboration with Revit (pictured), IFC, BCF 3.0 and IDS format, a protocol for enabling the construction sector to establish and validate BIM specifications 4 Graphisoft’s collaboration and presentation tool, BIMx, now supports antialiasing, leading to better quality model edge definition

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■ www.graphisoft.com

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Feature

Bentley Systems the promise of data freedom Many of the major AEC software firms talk openness, but as the industry shifts from file-based systems to data lake environments, none inspire as much confidence as Bentley Systems in ensuring that customers will retain full control of their data now and well into the future, writes Greg Corke

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entley Systems wasn’t wasting sage should resonate more than ever. engineers, constructors, and organisatime at its recent YII conference, With proprietary files (DWG / DGN / tions maximise the value of their data. hammering home its ‘open’ RVT) at least drawings and models could “We’re not keeping it to ourselves. We approach to data. The message be accessed via Open Design Alliance actively encourage others in the industry from Bentley’s execs was clear: the com- (ODA) libraries. With proprietary data- to adopt the schema. This is about movpany is putting its weight behind open- bases, access is granted only via APIs, ing the entire infrastructure sector forward together.” ness— the subtext being that some of its which are under the control of the vendor.

“We are not creating another silo,” competitors are not.

Artificial Intelligence (AI) The emphasis was hard to miss. In the said Cumins.

Looking ahead, Bentley is focused not Cumins described AI as a “paradigm first two keynote presentations alone, led by new CEO Nicolas Cumins and CTO just on the present, but on the long-term shift” for the infrastructure sector, highJulien Moutte, the word ‘open’ was used future. Infrastructure is built to last. “Our lighting the massive scale of data generusers must assure that this data, their ated during the design, construction, and a staggering 60 times.

While AI also got a strong showing data, remains accessible for decades to operational phases. “It makes infrastrucwith 47 mentions, it was obvious that come, and we believe this is only possible ture a prime area where AI can have the Bentley was speaking to customers, and with a truly open approach,” said Moutte. greatest impact,” he said.

At the heart of Bentley’s open strategy not trying to impress investors. The mesBentley’s investment in AI dates back sage? Openness isn’t just a token word; is the iTwin platform, a suite of APIs and several years. In 2018, the company it’s a cornerstone of Bentley’s strategy. services designed to help AECO firms acquired machine learning and IoT devel“Your data is your data oper AIworx, which always,” said Cumins. former CTO Keith Moutte outlined the Bentley described as an three pillars of Bentley’s Bentley made its open stance abundantly clear with “acqui-hire,” meaning it open approach: open executives using deliberate, impactful messaging: was made primarily for standards where every“Don’t get locked in,” “Your data is your data,” and the talent. Since then, body that was granted that talent has driven “We’re not creating another silo.” access to the data can several successful AI read and understand it; use cases, primarily in open source, where asset operations. These every developer can leverage that data; develop digital twin applications for include automatic object classification in and open APIs, where users are free to designing, building, and operating infra- reality meshes and using computer take their data out whenever they want, structure assets. iTwin integrates data vision, IoT sensors, and machine learning from various sources—specs, drawings, for predictive maintenance—detecting instead of just being able to query it.

Cumins also touched on the complexity CAD and BIM models, reality captures, issues before they lead to failures. of infrastructure projects, which involve sensor data, inspection records, and more.

Many of these technologies now fall The platform is built on a schema spe- under Bentley Asset Analytics, a new multiple organisations, teams, and disciplines “This complexity makes it impos- cifically designed for infrastructure. product line that uses AI to provide sible for you to rely on any single system While the majority of this schema is insights into the condition of infrastructure or single vendor. Instead, you need an open-source, one component — the assets. “This approach is especially imporecosystem that enables flexibility, inte- Parasolid geometry modelling kernel —is tant for critical infrastructure like bridges gration and interoperability across dif- proprietary, as it is owned by Siemens. and dams, where monitoring and mainteAs Cumins explained, “The schema nance are key to ensuring long-term safety ferent tools and platforms,” he said.

He also addressed a common concern goes beyond basic data exchange, ensur- and performance,” said Mike Campbell, among customers: “Don’t get locked in,” ing that data isn’t just accessible, but its Chief Product Officer, Bentley Systems. he said. “Make sure you retain control of meaning can also be understood, whethThe portfolio includes Blyncsy, which er you’re dealing with materials or struc- utilises crowd-sourced dashcam footage your data.”

As AEC firms navigate the transition tures or subsurface data.” and machine learning models to autoHe emphasised that this schema helps mate roadway maintenance and asset from files to a data-lake world, this mes-

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Nicolas Cumins, Bentley Systems CEO, on stage at the Year In Infrastructure event in Vancouver

inventory. “AI can help identify roadside assets and assess their conditions, everything from a broken stop sign to a faulty streetlight to a fresh pothole,” explained Mike Schellhase, VP of asset analytics at Bentley. “These insights feed directly into the infrastructure digital twin, the iTwin, and are presented in iTwin Experience to show the latest conditions and context.”

Another product, OpenTower iQ, uses drone imagery, data, and AI to manage telecom towers throughout their lifecycle, handling everything from data acquisition and visualisation to structural analysis, site design, and maintenance.

Bentley plans to expand these solutions to cover a broader range of asset types, offering owner-operators increasingly advanced AI-powered tools.

Now, the company is pushing AI further into the design phase, using generative AI to automate repetitive tasks.

The first of a new generation of AI-powered design tools is OpenSite+, which is used for civil site design (including roadways, parking lots, and buildings).

The software features a co-pilot experience that taps into knowledge stored in documentation, specifications, and 3D site models through natural language interactions. “We can ask questions like, ‘Can I build a hotel in this area?’ or ‘Do I have enough parking to meet my requirements?’” said Francois Valois, VP of civil infrastructure at Bentley.

“At this stage [in the design process], we don’t know if our layout is optimal, so we build a neural network that evaluates thousands of alternatives to find the best one, optimising costs while meeting engineering requirements,” Valois explained.

The software also offers AI-powered earthwork optimisation, which Bentley has enhanced by wrapping its current engine in a neural network to make the process significantly faster.

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save so much time and money (read this AEC Magazine article - www.tinyurl.com/AECdrawing). According to Bentley, drawing production can account for up to 50% of a site design project’s time, and Bentley’s AI-powered tools automate annotation, labelling, and sheeting, optimising the placement of labels and dimensions, and according to organisational standards.

Currently, drawing production isn’t built directly into OpenSite+, but rather, it’s routed through OpenSite Designer, an existing power-platform based product based on MicroStation. However, as Campbell explained, by going down this route, the technology can then be made available in other power platform-based applications. Watch this space.

This process will take time, as the large language model (which Campbell playfully wants to call a “large drawing model”) has so far only been trained on tens of thousands of site plans and only from North America. “We’ve got to do that for the UK, for Australia, for all of the other places, because the standards are all different,” Campbell said. “Roadway plans have a different look and feel, right? So, we’ve got to build a model for that.”

As to where the training data has come from, Campbell explained that most of it is sourced from a licensed open-source library, though some customers have granted Bentley explicit permission to use their data. “We’re not just going and taking plans from random [customer] accounts,” he said, adding that Bentley keeps track of the provenance of every data set used. If a company decides to withdraw its data, Bentley will retrain the model accordingly.

In the future, customers will be able to train the AI model on their own data.

“Say you’ve got 6,000 site plans—you can put them into your own local, retrained version of the model, and that will be yours and yours alone.”

As for the future of AI at Bentley,

Campbell hinted at broader applications.

“Instead of using AI to generate a site, could we use AI to generate other designs, a bridge design, for example, optimise a road for – not just the obvious ones like curvature and safety, but things like carbon impact and cost and time?”

“Civil engineers can imagine a certain section of the design space. AI can imagine a much broader design space,” Campbell added. “The good news is that in engineering, we’re governed by rules of physics and standards and safety factors and all those kinds of things, so that limits it, but still, it’s bigger than what a typical engineer can think about.”

Desktop deployment Beyond AI, one of the most significant aspects of OpenSite+ is that it’s a completely new type of application. It’s iTwinnative, so it writes directly to an iModel without needing to go through intermediary formats like DGN. Unlike many modern applications, it’s also a desktop application, rather than running in a browser.

“We’re not yet convinced that all of these engineering workloads are going to be able to work on the cloud,” explained Campbell. “We also want to be able to take advantage of local compute. And we’ve also got our eye on these new AI processors that are coming out – NPUs – and we want to be able to take advantage of that.”

OpenSite+ works both online and offline, syncing changes (deltas) when connectivity is restored. Bentley is taking the same desktop/iTwin-native approach with its new visualisation tool, Advanced Visualization, which is built on Unreal Engine (more on this later).

Campbell acknowledges that more tools are in the pipeline, either going through validation or still in the research phase, and they will all follow this same framework.

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Bentley’s acquisition strategy. “Not necessarily, but it would be a consideration,” he said. “We certainly look at architecture [of the software].”

He also admitted that technical integration has become a key focus for Bentley, which is one reason why acquisitions have slowed over the last couple of years. The priority now is ensuring that products work seamlessly together.

“The idea of convergence and integration, ensuring that data flows smoothly across applications and the lifecycle, and informs the infrastructure digital twin— that’s the goal,” Campbell emphasised.

Back into BIM?

effectively changing the vantage point of an infrastructure digital twin, from the engineering model of the infrastructure asset to the planet Earth, upon which we geolocate the engineering model and all the necessary data from the surrounding built and natural environments.”

However, as Cumins explained, perhaps the most significant aspect of the acquisition is that Cesium, as a company, perfectly aligns with Bentley’s vision of open standards and interoperability.

“The combination of Cesium plus iTwin enables developers to seamlessly align 3D geospatial data with engineering, subsurface, IoT, reality, and enterprise data to create digital twins with astonishing user experiences that scale from vast infrastructure networks to the millimetreaccurate details of individual assets— viewed from land, sky, and sea, from outer space to deep below the Earth’s surface to support engineering workflows.”

Cesium’s 3D Tile technology makes light work of huge geospatial datasets by streaming only what the user needs for any given view.

It uses a concept called hierarchical level of detail (HLOD), where you basi-

Building on this geospatial focus, Bentley announced a new strategic partnership with Google which will integrate Google’s comprehensive repository of 3D geospatial data with Cesium and Bentley’s iTwin platform.

“Consider a large urban development project where multiple infrastructure systems are used – roads, bridges, energy and water networks – that must be coordinated across various stakeholders,” said Cumins. “By integrating Google’s vast 3D geospatial data with Bentley Cesium technology and iTwin platform stakeholders can visualise their assets, both existing and plan in full real-world context.”

Advanced Visualization Bentley once held a strong position in architecture, especially in the early 2000s Cesium 3D Tiles and Google 3D Tiles with MicroStation and Generative play a key role in Advanced Components, a pioneering computational Visualization, a new product from design tool that preceded Grasshopper.

Bentley powered by Unreal Engine, However, in recent years, the company designed to overcome the challenges of has shifted its focus away from this marcreating immersive, interactive, and phoket. Given the growing interest in nexttorealistic infrastructure experiences. generation BIM tools, the question arises: This software integrates seamlessly does Bentley have aspirations to get back with iTwin for live access to up-to-date into BIM? project data, enabling users to navigate “Our focus right now is absolutely on massive models in real time using horizontal infrastrucCesium 3D Tiles. ture, and there’s plenAs Greg Demchak, ty there to keep us VP, emerging techThe long-term plan is to unite the iTwin and Cesium busy,” said Campbell. nologies group at Ion platforms, but as Patrick Cozzi, CEO of Cesium and Bentley explained, “But I’m reluctant to say never, espe- now chief platform officer at Bentley explained, nothing users can enrich cially in light of the their scenes with will be done without input from the community sentiment of the additional context broader AEC ecosysand content: tem. In particular, “Context in the form I’m thinking about open letters, I’m cally have a tree of tiles – the root being of Google 3D tiles, and content in the thinking about the AEC spec [AEC the least detailed version, the branches form of easy to place trees, cars, scale, figFuture Software Specification]. I’m think- adding more detail, and the leaves hav- ures and equipment.” ing about what their vision is for the tools ing the highest resolution.

Advanced Visualization functions either 3D Tiles can handle a whole smorgas- as an out-of-the-box solution or as a flexithey’ll use in the future. And I’m thinking about the tools that we’re building. And bord of 3D geospatial data including point ble platform for building custom applicawhen I read that spec and I look at our clouds, reality models (derived from pho- tions and is currently in Early Access. strategy, it’s not dissimilar. It’s not a slam togrammetry), and 3D buildings.

Through its recent AECO Tech Preview Up front carbon analysis dunk, but we’re in the ballpark.

“The data lake, the elements of open- Program it can also handle BIM models One of the key challenges in achieving ness, design in context and at scale. (IFC and Autodesk Revit), complete with sustainability on infrastructure projects metadata which can be used for querying, is the time-consuming nature of carbon That’s in the AEC spec.” filtering, styling, and analytics. reporting, which is typically handled by Geospatial – giving assets context The long-term plan is to unite the specialists.

Kelvin Saldanha, associate director at In September, out of the blue, Bentley iTwin and Cesium Ion platforms, but as Systems acquired Cesium, developer of Patrick Cozzi, CEO of Cesium and now WSP, elaborated: “Once you’re ready to an industry cherished 3D geospatial plat- chief platform officer at Bentley measure carbon, it needs to go through a form – Cesium ion – with an ecosystem explained, nothing will be done without rigorous quantity take-off process, of open standards, including Cesium.JS input from the community. The potential including design compilation and data and 3D Tile technology. (To learn more is limitless, he said. “We can add voxels cleansing, before that data can be used in about the acquisition read this AEC Magazine for biometric visualisation, for subsur- third-party software.” face, we can add Gaussian splats for This process can cause significant article www.tinyurl.com/geo-whiz).

“With the acquisition of Cesium, we are higher visual quality for point clouds; we delays. As Saldanha noted, “A lot of now able to provide a 3D geospatial view can do temporal tiles to help show the times that delay means that the design team doesn’t know what the carbon score of infrastructure,” said Cumins. “We are change in construction sites over time.”

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Feature is until the design is very mature, and you kind of miss the opportunity to reduce your carbon score.”

He emphasised that the best opportunity to make a meaningful impact on carbon reduction is in the early stages of a project’s design cycle.

WSP has been testing new carbon analysis capabilities in iTwin Experience through Bentley’s Early Access Program, which Saldanha said gives the design team much-needed transparency in the earlier phases of a project. “Continuous calculations during the design process allow for accurate carbon reports to be generated much earlier in the project lifecycle,” he added.

What truly sets Carbon Analysis apart, according to Saldanha, is the software’s visualisation capabilities. “Instead of sifting through spreadsheets and tables, designers can now exchange data directly with EC3, view heat maps, and interact with them to quickly identify where they’ve got carbon intensive features on their project, and then they can target those.”

Bentley’s new Carbon Analysis capabilities are available to iTwin Experience users at no additional cost, though a separate licence is required for carbon assessment calculators like EC3 or OneClickLCA.

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Conclusion While many AEC software companies talk openness, few demonstrate the same level of commitment as Bentley – though open standards, open source and open APIs. At YII, Bentley’s executives made this abundantly clear with deliberate, impactful messaging: “Don’t get locked in,” “Your data is your data,” and “We’re not creating another silo.”

This was a strong signal to customers that the keys to their data must remain in their hands, a crucial point as the AEC industry transitions from file-based systems to data lake environments.

Of course, Bentley’s approach isn’t purely altruistic; as a company with shareholders now, it stands to benefit from the industry moving towards storing data in its model wrapper. And while third parties can choose to use the open specification to create an iModel / iTwin independently, Bentley has a suite of mature data management, authoring and analysis tools and services ready to go.

But with this open approach it’s clear that Bentley is playing the long game—a smart strategy considering the long lifecycle of infrastructure assets.

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will evolve considerably over time. “So, by ensuring that our systems remain open, we allow organisations to adopt new technologies and innovations while still being able to access and build on their historical data,” he said.

Of course, it’s possible that future platforms may not even be developed by Bentley, but the key takeaway for customers investing in the Bentley iTwin ecosystem is this: they will always have the freedom to choose.

■www.bentley.com

1 Bentley OpenSite+ with copilot uses organisation-specific documents and design models for quick insights and edits 2 Bentley OpenSite+ uses Al to automate annotation and plan production for civil site design 3 Bentley’s Carbon Analysis capabilities: Embodied carbon grouping of common components for reporting

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Feature

BHoM - addressing the interoperability challenge The BHoM computational development project allows AEC teams to improve project collaboration, foster standardisation and develop advanced computational workflows, as Buro Happold’s Giorgio Albieri and Christopher Short explain

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n Buro Happold’s structural engineering team, we’re constantly working on unique and challenging projects, from towering skyscrapers to expansive stadiums, intricate museums to impressive bridges.

Our approach is all about exploring multiple options, conducting detailed analyses, and generating 3D and BIM models to bring these projects to life.

But this process comes with the major challenge of interoperability - the ability of different systems to exchange information.

Since we collaborate with multiple disciplines and design teams from all over the world, we regularly deal with data from various sources and formats, which can be a real challenge to manage.

The AEC industry often deals with this by creating ad-hoc tools as and when the need arises (such as complex spreadsheets or macros). But these tools often end up being one-offs, used by only a small group so we end up reinventing the wheel again and again.

This is where the BHoM (Buildings and Habitats object Model) comes into play, a powerful open-source collaborative computational development project

for the built environment supported by Buro Happold.

BHoM helps improve collaboration, foster standardisation and develop advanced computational workflows.

Thanks to its central common language, it makes it possible to interoperate between many different programs.

Instead of creating translators between every possible combination of software applications, we just need to write one single translator between BHoM and a target software, to then connect to all the others.

enhanced our approach to structural design.

Once the architectural model is received, using the BHoM we can quickly and precisely build several Finite Element Analysis (FEA) structural models for conducting structural analyses.

It’s possible to clean and rationalise the original geometries for specific purposes and assign/update attributes to all objects based on the results of both design and coordination with other disciplines.

Finally, the BIM model of the structure can be generated in an algorithmic manner.

The solution: The BHoM

BHoM in practice

The BHoM consists of a collection of schemas, functionalities and conversions with the following three main characteristics:

It’s often thought that computational and parametric design is only applicable to the very early stage of a project that relies on very complex geometry.

The reality is, computational design is greatly beneficial at every stage: from the conceptual feasibility study to the detailed design of steel connections.

At Buro Happold, we use the BHoM to help us address multiple stages throughout a project, as demonstrated in the following case study examples which focus on the re-development of a desalination plant in Saudi Arabia into a huge museum.

• It attempts to unify the “shape” of the data • It is crafted as software-agnostic • It is open source so that everyone can contribute and use it Currently, the BHoM has over 1,200 object models with an extendable data dictionary and adapters to over 30 different software packages.

With the BHoM, we’ve refined and

Flowchart of typical BHoM-based computational workflow on projects

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Modelling the existing and the new Let’s see how a computational workflow applies to the modelling and analysis of existing structures making use of the BHoM. For the Saudi Arabian project, all we had was a set of scanned PDF drawings of the existing structures.

Within a couple of months, we had to build accurate Finite Element Models for each of them and run several feasibility studies against the new proposed loadings.

A parametric approach was vital.

Therefore, we developed a computational workflow that allowed us to create the geometric models of all the built assets in Rhino via Grasshopper by tracing the PDF drawings, assigning them with metadata and pushing them via BHoM into Robot to carry out preliminary analyses and design checks.

Of course, there’s no need to mention how much time and effort this approach has saved us compared to a more traditional workflow.

Moving on to the next stage of the project, we needed to test very quickly many different options for the proposed structures, by modifying grids, floor heights, beams and column arrangements, as well as playing with the geometry of arched trusses and trussed mega-portals.

Again, going for a computational approach was the only way to face the challenge and we developed a largescale algorithm in Grasshopper.

By pulling data from a live database in Excel and making use of an inhouse library of clusters and textual scripts, this algorithm was able to leverage the capabiliwww.AECmag.com

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ties of the BHoM to model the building parametrically in Rhino, push it to Robot for the FEA and finally generate the BIM model in Revit - all in a single parametric workflow.

Managing data flow: BIM – FEA

One-to-one connection approach between software packages (above) vs direct connection to BHoM centralised softwareagnostic environment (below) highlighting current collection of main BHoM adapters

As we move into later stages of the project, the more we can see how computational workflows are not only beneficial for geometry generation but also for data management and design calculations.

At Stage 03 and 04 we needed to be able to transfer and modify very quickly all the huge sets of metadata assigned to any asset within our BIM models while being able to test them on a design perspective in Finite Element Software.

Again, we developed an algorithm in Grasshopper leveraging the BHoM to allow for this circular data flow from BIM to analysis software - Revit and ETABS in this instance.

This made it possible to test and update all our models quickly and precisely, notwithstanding the sheer amount of data involved.

Interdisciplinary coordination As usual, when moving forward in the project, coordination with MEP engineers starts to ramp up and when structures are big and complex, it becomes even more difficult.

The challenge we had to face was intimidating.

We had eight concrete cores, 45m tall, more than 9,000 Mechanical, Electrical and Plumbing (MEP) assets for the building and around 1,500 builderswork openings to be provided in the core walls to allow them to pass through.

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Feature

1 Graphical representation of the algorithm for the automated creation of builderswork openings in the concrete cores of the building

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2 Algorithm for the computation and documentation of the connection forces with textual and graphical outputs

On top of this, we had the need to specify openings of different sizes depending on different requirements based on the type of MEP asset, as well as the need to group and cluster openings based on their relative distance and other design criteria.

Again, a high level of complexity and a huge amount of data to deal with. Indeed, a computational approach was needed.

Using Grasshopper, BHoM and Rhino.

Inside Revit, we developed an algorithm, graphically represented in Figure 6.

Through grouping operations, model laundry algorithms and the parametric modelling of the builderswork openings, we were able to generate parametrically the BIM model of the cores provided with the required builderswork penetrations.

In parallel with this, the algorithm also generated the corresponding FE model of the core walls, so the structural feasibility of the penetrations could be checked before incorporating them in Revit.

The algorithm detected the intersections between pipes and walls, then generated openings around each intersection of different size and colour depending on different input criteria. Then, using a fine-tuned grouping algorithm, it clustered and rationalised them into bigger openings, wrapping all of them together based on user-input criteria.

Finally, after testing the openings in the Finite Element software, the algorithm pushed them into Revit as Wall Hosted Families and a live connection between the Rhino and the Revit environment streamlined any update process in parallel.

Producing large data sets Moving even further into detailed design, the amount of data to deal with on a project of such scale becomes more and more overwhelming.

This is what we had to face when deal40

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ing with the design of the connections.

Although the design was subcontracted to another office, we faced the challenge of providing all the connection design forces in a consistent and comprehensive format, both in textual and graphical contexts.

Indeed, this is not an easy task, especially when dealing with around 35,000 connections, 60 load combinations, 2,000 different frame inclinations, six design forces per connection and spanning over three different finite element software packages (ETABS, Robot, and Oasys GSA).

We had to deal with 12.6 million pieces of data and we had to do it very quickly, being able to update them on the fly. Again, a computational workflow was required.

Via Grasshopper and the BHoM, we developed an algorithm to extract, postprocess and format the connection forces from the Finite Element models of all the assets of the project, serialise them in JSON, save them in properly formatted Excel files and show them graphically in corresponding Rhino 3D models via tag-

ging and attributes assignment.

All this information was sent out for the design to be carried out by other parties.

Conclusions Applying a specialised approach, relying on algorithmic methodology and leveraging state-of-the art computational tools, such as the BHoM, enable us, at Buro Happold, to deliver comprehensive and advanced structural solutions, ensuring efficiency, sustainability, and optimal performance across all the stages of the project.

Resources [1] BHoM Documentation (2024): https://bhom.xyz/documentation [2] LOMBARDI, Alessio, (2023), Interoperability Challenges. Exploring Trends, Patterns, Practices and Possible Futures for Enhanced Collaboration and Efficiency in the AEC Industry, in www.researchgate.net, London, UK. [3] ELSHANI, Diellza, STAAB, Steffen, WORTMANN, Thomas (2022), Towards Better Co-Design with Disciplinary Ontologies: Review and Evaluation of Data Interoperability in the AEC Industry, in LDAC 2022: 10th Linked Data in Architecture and Construction Workshop, Hersonissos, Greece.

www.AECmag.com

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Speckle matures Speckle is accelerating development of its collaborative AEC data hub, replacing clunky file-based processes with powerful new workflows that connect hitherto incompatible BIM tools, writes Martyn Day

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peckle began as a research project during Speckle founder and CEO Dimitrie Stefanescu’s PhD studies at University College London.

It evolved into an ‘insider’ industry hack, with Speckle COO and cofounder Matteo Cominetti experimenting with the technology during his time at Foster + Partners.

The goal was to find alternative methods for sharing, querying, and viewing BIM models -circumventing proprietary lock-ins, developer APIs, cumbersome ‘everything’ file transactions, and centralised file servers.

From its interoperability beginnings, a community grew, and Speckle eventually secured funding to establish itself as a standalone company to accelerate development.

Initially catering to a coding-savvy audience of AEC experts, hackathon enthusiasts, and BIM developers, Speckle has since evolved into a suite of tools and workflow capabilities which can be deployed to drive and automate bespoke project processes. This has helped make Speckle accessible to a much broader audience.

Connect Speckle is built around the concept of connectors, applets that sit inside commonly used AEC applications that open-up their data to be streamed into and out of a centralised, open granular model (or Common Data Environment - CDE).

These connectors act as an industry wiring harness, bridging applications from different developers that don’t share APIs or struggle to write reliable common open data file formats.

Speckle supports plenty of formats:

Revit, Rhino, Blender, Excel, Grasshopper, PowerBI, SketchUp, Dynamo, Navisworks, AutoCAD, Tekla, ArcGIS, Unreal, Unity, among others. If a connector isn’t available, those with the necessary skills can create their own. We understand Tesla wrote one for Dassault Systèmes Catia.

Collab The next component is the Speckle central data hub, which handles data, federated project data and teams. Speckle can be hosted in any region or country to meet customer preferences or for compliance requirements. Alternatively, Speckle can host it for you.

Model and project data from all disciplines are streamed in real time to a central project Speckle Workspace, where the model definition can be composed, with overlays, offering view manipulation, filters, comment / discussions, measure etc. Everything is done through a simple-to-use browser-based Speckle viewer, which can also be set to synchronise views between users during collaborative meetings (follow mode).

Team members can now be assigned varying levels of access, whether to entire projects or specific permissions within them. Powerful capabilities include realtime tracking of model changes, down to individual elements. Users can see which objects were removed, added, modified, or remain unchanged.

The new deployable Workspaces and Teams features mark the beginning of Speckle’s move toward offering turnkey project hosting solutions for a broader

range of BIM firms - especially those without the in-house expertise to shape and craft a Speckle server workflow or Teams deployment.

This will bring Speckle into contention with relatively high-priced project management BIM tools and cloud hosting services. See later for the business model.

Automate Speckle launched ‘Automate’ in beta last year (read this AEC Magazine article – www.tinyurl.com/Speckle-AEC) which it describes as a CI/CD solution, offering Continuous Integration (CI) and Continuous Delivery (CD).

Automation loops and processes can be triggered whenever a model changes. For example, if an object in an architectural model is edited, Speckle Automate can automatically run clash detection with geometry from all disciplines in the background, perform quality assurance or code compliance checks, generate reports, or run analyses. Everything is fully customisable - it’s totally down to how each firm wants to architect the automation.

As Speckle can pretty much talk to any API, loops can cross application boundaries, integrating customers’ tech stacks to work as one using Python and .NET. Over the past year, Speckle recognised that some automation routines were too complex for non-coders. In response, significant improvements have been made to the user interface, making it more accessible and intuitive for project teams.

Additionally, Speckle now offers templates for common functions. It appears

Speckle Con: sharing solutions to real world problems At the recent Speckle Con event in London, presentations were dominated by users showcasing the wide range of innovative ways in which Speckle has been deployed.

From refining internal processes and developing custom automations to augmenting BIM data with fabrication data, solving structural challenges, and creating new cloud-

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based applications, the event highlighted the versatility of the platform for solving real world problems. Attendees also demonstrated how they integrated AI into workflows, collaborated on road and rail civil projects, coordinated project teams, and embedded an opensource Life Cycle Assessment (LCA) capability across their practice.

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Speakers came in from all around the world: RHDHV, Herzog & de Meuron, BaneDanmark, Perkins and Will, Ramboll and LINK Arkitektur, to name but a few. The presentations will be available online soon and we highly recommend watching them all.

Of particular note was Frederico Borello from Encode, who demonstrated how Speckle served as a

powerful connector, bridging the gap between low level of detail architecture to high level of detail fabrication.

Also worthy of mention was Jordana da Castro Rosa and Adam Burnham of Perkins and Will, who used Speckle tech to develop tools that could possibly be commercially sold, all originating out of AEC hackathons.

■ https://conf.speckle.systems

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that Speckle Automate will soon leave beta and become a supported product.

The formulation of Workspaces, Teams and Automate, together with the established connectors and mode hub, has enabled the company to streamline its offerings.

Speckle has traditionally operated with what could be considered a “suicidal business model,” offering everything as open source. The company’s revenue primarily came from those who chose to pay for Speckle server hosting — yet, they were never required to do so.

With the attraction of venture capitalists and development money (Speckle recently raised $12.5m) the company is shifting towards a more sustainable business model. That said, even with this change, the prices we’ve seen for the capabilities on offer remain an absolute bargain.

There are still free options for individuals, open-source software, and customers can opt to host their own Speckle servers.

However, the Workspaces and Automation capabilities will come at a cost per user and are not ‘open source’. There will be three Workspace plans that differ in security options, starting at £12 per seat, per month, rising to £60 per seat, per month with SSO and data region of choice.

Once ‘Automation’ comes out of beta, there will be charges based on automation instances, although a certain amount of usage will be built into enterprise plans.

Conclusion Speckle continues to support its community by maintaining a free point of entry, while also developing advanced tools that simplify deployment. This approach should appeal to a wider range of firms, especially those with limited coding knowledge in house —previously a potential barrier to entry.

This all goes a long way to make Speckle a modern software company with a turnkey product to sell. There’s still lots of flexibility as to how it’s wired into company and project workflows, but it will be liberating for any project to step outside the silos of their BIM 1.0 tool sets.

In many ways Speckle is a low-cost retrofit that will allow existing software tools to deliver next generation granular, multi-disciplinary workflows, without compromising long grafted in-house skills on mature software. At the same time, it frees project data from proprietary software locked behind shareholder-driven pricing models.

Speckle could well go from being the secret sauce of the BIM illuminati to becoming the champion silo slayer for all project fiefdoms. It’s just too useful for the industry to ignore.

■ www.speckle.systems

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Software

HP Build Workspace connecting site with office Since launching its SitePrint robot in 2022, HP Construction Services has shifted focus to software, with a cloud platform that boosts collaboration, streamlines site reporting, and uses AI to vectorise legacy construction drawings, writes Greg Corke

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n construction, it’s easy to get swept up in the buzz around emerging technologies like robots, drones, reality capture, XR, and AI. Yet, despite these advancements, significant inefficiencies remain in everyday workflows – particularly in how the industry manages and collaborates on documents and drawings.

While established project management platforms like Procore and Autodesk Construction Cloud (ACC) offer more sophisticated solutions, HP sees a gap in the market for a simpler, more cost-effective alternative. Enter HP Build Workspace, a new cloud-based platform developed by HP’s Construction Services Division in Barcelona, which works closely with the company’s DesignJet large-format printing team.

“We identified that there were a lot of people that just weren’t using those tools [Procore, ACC] precisely for those reasons [cost, complexity], and therefore there was an opportunity to really simplify the process,” explains Daniel Martínez, global head and general manager, HP large format.

HP Build Workspace aims to tackle a range of common pain points in construction, from managing and distributing drawings to documenting site visits, generating site reports, and converting legacy drawings into editable vector CAD files.

The team behind HP Build Workspace spent several months embedded at construction sites to better understand workflows and pinpoint areas for improvement. One key observation was the timeconsuming and fragmented way site conditions and issues were documented and communicated, as Martinez explains, “[They are] basically taking photos on their phone, going back to their office, downloading the photos onto their desktop and sorting them out. They’re then 44

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spending hours preparing the reports.”

With HP Build Workspace, photos taken on-site can be immediately linked to specific locations on floorplans through an iOS or Android mobile app, significantly simplifying documentation.

Observations can be categorised, augmented with text or voice notes and then automatically fed into reports that can be shared easily with other project members.

HP Build Workspace provides a centralised hub for document management, enabling teams to access files / drawings from anywhere. Everything is managed through the cloud platform, ensuring a single source of truth and providing an audit trail. In contrast to relying on isolated communications via WhatsApp or

email, all stakeholders are directed to the platform via a link. In the future, HP Build Workspace will also be able to sync to cloud storage services including Google Drive, Dropbox and OneDrive.

A new life for legacy drawings Perhaps one of the most innovative aspects of HP Build Workspace is its ability to convert legacy construction drawings into CAD-editable vector files with much higher accuracy than before.

“It’s a big pain point today,” explains Martinez, adding that most companies ship their PDF or scan files overseas, or hire drafters locally. “It’s a very expensive process, very time consuming,” he says.

“We scan millions of drawings a year, and [automatic conversion] is a service that our customers have been asking for, for years. We just hadn’t necessarily focused on it or felt that we had the right technology to address it the way that we felt that it should be addressed,” explains Martinez.

The technology that Martinez is referring to is, of course is AI, specifically machine learning (ML).

HP has been refining the AI behind this capability for over three years, using a combination of real-world customer data and synthetic files to train its models. The system applies a combination of AI models – some remove noise from the initial image, others separate different elements into layers.

“We have very high accuracy on certain types of CAD files,” says Martinez.

“Imagine old archive drawings that have a lot of image noise in them, or are not very, very clear as you get them scanned, we can apply ML to get a higher level of accuracy than anything existing on the market today and the more people that use it, the more accurate it gets.”

The system can detect lines, polylines, arcs, and text. Once text has been extracted and indexed, users can search on that data. Outside of HP, there are several AI systems currently in development that enable firms to use Large Language Models (LLMs) to make sense of and recognise patterns within large sets of unstructured data. It’s hard to imagine that HP isn’t planning something similar with the data extracted from drawings, such as title blocks, notes and dimensions.

The conversion service comes with a simple editor. Here users can change lines that were incorrectly converted from dashed into solid, connect lines that should have been snapped together, as well as clean, remove or add elements. This isn’t just to improve the quality of individual www.AECmag.com

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HP Build Workspace uses AI to convert legacy construction drawings into CAD-editable vector files with much higher accuracy than before

documents – all this information gets fed back into the system to improve the AI. “The customer can define if it’s accurate enough for them, and we get real time feedback from that,” says Martinez.

Customers get to choose to opt-in or not, but as Martinez explains, HP only looks at the process. “The fact that you’re sharing the files for ML doesn’t mean that we have access to the content in any way, shape or form,” he says.

By tracking conversions, HP can understand what percentage of files have been accepted by the customer and, as new versions of the training model are released, if it’s improving or not. Martinez admits there have been cases when the success rate went down. “We’ve then been able to course-correct and eliminate whatever it was in the system that was affecting the quality of the output,” he says.

The big question is: will things ever get to a stage where the end user doesn’t have to check for accuracy?

Martinez responds, “PDF files that were converting back into vector that have that vector layer information embedded? Yeah, we’re very close to 100%. If it’s a very old drawing that’s done by hand, the success rate is obviously much lower than if it’s a very clear line drawing that we can convert quite easily.”

Physically connected to site HP Build Workspace also integrates seamlessly with HP SitePrint, the threewheeled robot that prints 2D plans directly onto construction site floors, with a view to replacing slow, error-prone manual layout processes (read this AEC Magazine article - www.tinyurl.com/HP-siteprint).

The aim is to enable general contractors, specialist contractors, and construction management firms to quickly and accurately set out the locations of building components. This streamlines site preparation, ensuring everything’s ready for the various trades to come in. www.AECmag.com

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Since its launch in 2022 there have been several improvements to the technology, including the recent addition of a Revit plug that allows SitePrint-ready plans to be exported from the popular BIM authoring tool.

The new HP SitePrint Value Pack 3.0, announced this month, is said to deliver a 30% boost in print efficiency compared to its predecessor, which had already introduced similar performance enhancements earlier this year.

Most of these improvements are around navigation – moving from A to B – which is how the robot spends much of its time.

Previously, it did this at 0.4 m/sec, but now it’s nearly doubled to 0.7 m/sec.

Meanwhile, the print speed has

seen a s l i g h t increase, from 0.33 m/ sec to 0.35 m/sec.

HP Smart Navigation gives the robot a new integrated front-facing camera which creates a 3D representation of the robot’s surroundings, allowing it to detect unmapped obstacles on the job site and intelligently adjust its navigation route in real-time.

HP SitePrint Value Pack 3.0 also introduces shadowing, a new feature designed to prevent the robot from navigating into areas where it might lose line of sight with the robotic total station.

HP is also turning the robot printer into a device that can be used for reality capture. It is working with HP SitePrint customers on a proof-of-concept to check surface flatness, to help ensure surfaces are

ready for construction. And it can do this while printing. For example, it can measure the flatness of a drywall / partition track, and then print notes in reference to the corrections that need to be done when installing on site.

The HP Reality Capture Technology Flatness Check will be sold as a service for HP SitePrint through subscription and is due to launch in 2025.

Conclusion When HP Build Workspace was announced last week, it raised a few eyebrows. Does the AEC industry really need another collaboration platform, and will HP be stepping on the toes of established players?

The reality is that many AEC firms still rely on manual workflows, and these are the companies HP is targeting. The goal is to streamline and automate familiar processes like document distribution, site reporting, and vector conversion—bringing efficiency to areas where it’s often lacking.

That said, there are some gaps in the current offering. For instance, there are no built-in drawing markup tools, and while users can annotate plans with notes and site photos, it would be even better if these were automatically geolocated.

Of course, there’s significant potential for future enhancements. Right now, the platform focuses largely on 2D workflows, but could it evolve to support BIM workflows? Instead of just a camera, could it use a smartphone’s LiDAR sensor to capture site conditions as 3D meshes? And could reality capture with SitePrint extend to basic construction verification?

While some competitors offer more advanced features like these, it seems likely that HP will stick to simplicity.

After all, many AEC firms are still wrestling with getting the fundamentals right, and HP Build Workspace might just be what they need to bridge that gap.

■ www.build.hp.com

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Dalux ‘Hygge’ The history of Common Data Environments (CDEs) has been long, with many twists and turns. CDEs were necessary because BIM tools made huge files and developed deep silos to inhibit collaboration. The CDE developers who survived have gone on to build broad platforms to liberate design and construction data far and wide. Dalux is one of those firms, as Martyn Day reports

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stablished in 2005, Dalux is a Danish software firm which has created a digital platform for almost everything outside of BIM authoring tools. It focuses on information management, design management, model validation, tendering, site inspections, and snagging, for construction firms, developers and consultants. Dalux’s software expands through the lifecycle to data handover and facilities management. The company is also scaling up into infrastructure and GIS. Dalux started off creating what it claims to be the fastest BIM model viewing tool, being first to apply games technology to BIM geometry, an early entry into what is now the Common Data Environment (CDE) market. From that initial product Dalux has built a whole platform around its centralised data model, expanding to mobile and augmented reality.

Dalux now has a global user base of over 1 million professionals across 147 countries. Despite its scope and reach, the company is very much headquartered in Copenhagen, Denmark, which is the centre of operations and development.

The company has an annual user meeting, the Dalux Summit, which is hosted in Copenhagen. This year AEC Magazine attended to delve deeper into the products and the community. With over 1,800 attendees, the scale was much larger than we anticipated and the whole vibe was a unique experience.

Dalux feels like a family business and the dialogue and interactions between customers and the team gave the distinct

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impression that development of features and capabilities was a much more interactive process than at other software companies. Dalux has ‘Hygge’, a Danish word that roughly translates to ‘cosiness.’

The family business is run by two brothers, Torben and Bent Dalgaard.

Torben is the CEO and Bent is the CTO. In their morning address to attendees, one slide caught the zeitgeist perfectly - the brothers reassured the audience that Dalux is an independent software firm, that has no loans, no investors and is owned by Bent & Torben.

While many 19-yearold firms that have been growing 60% annually for almost a decade would be wafting share value, revenue or profit as an essential part of their mainstage moment, they opted to reassure customers that, unlike firms with shareholders that are repeat plunderers of their customers’ design technology budgets, Dalux is not in that game. There are

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very few AEC software companies with this attitude that come to mind – the most notable others being McNeel (Rhino) and Qonic.

The Dalux product family At the moment, Dalux offers nine products, which it has grouped in information management, onsite management and facility management, with almost half of its brands in on-site management.

BIM Viewer is free and works on desktop and mobile. It supports native BIM, IFC and drawings, with a range of free plug-ins for Revit, Solibri, Archicad, Navisworks and Tekla. It offers a suite of tools including measure, filter, properties, and make sections. Comments can be added, clashes from Solibri and Navisworks can be imported. We suspect that this is the gateway drug to the Dalux ecosystem!

Box is the core collaboration and CDE platform that delivers BIM geometry and data to collaborating project teams. It is accessed via the web browsers of supported mobile devices (iOS or Android).

Having extracted the data from the BIM authoring tool, Box centralises all the pro-

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1 Dalux has built a whole platform around its centralised data model, expanding to mobile and augmented reality 2 In their morning address to attendees the Dalgaard brothers caught the zeitgeist perfectly 3 Mapping the walks in Field Sitewalk, which enables the quick capture of a site using video from a helmet-mounted 360 degree camera

ject information in managed folders for design and construction teams to view, review and approve 2D and 3D data with individual team controls. Additionally, Box offers the ‘always requested’ clash detection, for both hard and soft clashes, as well as perform other geometry checks, such as point clouds from as-built.

Dalux Box Sync will download folders and files between the web and a local computer. It will also upload any files you want or have changed, making them available to other project participants.

model to see if the work is on track. The system offers some very clever registration between the rooms captured and generating the same view from the BIM geometry.

Infrafield is Dalux spreading its wings into the world of projects that span tens of kilometres, rather than metres with individual buildings. Given Dalux’s client list, we can well understand how Infrastructure became inevitable.

Infrafield required a new modelling engine technology to provide the expansive co-ordinate system. It supports 2D and 3D, Google Maps 3D tiles, drawings, GIS layers, terrain layers, and point clouds. Like ‘Field’ it can be used to track progress and capture issues. Users can create sections and cuts, measurements. It is seamlessly

asset tagging or room tagging. The system comes with workflow tools to route tickets to the right department or person.

Handover is the Dalux product for packaging up and handing over design, construction and associated project information post build. Using templates, Handover can save a lot of time making sure the right information is used for FM downstream. It can output PDF reports and COBie files.

Tender is the secure app for distributing tenders on projects through Dalux and Field is the product for quality control, integrates to Dalux Field. Tender bids health and safety, snagging/punch list and come with ready packaged up documents on-site reality capture. It brings the latest in a logical folder structure. The project drawings to site and assists in scheduling owner remains in control and Dalux proand managing site inspections with cusvides a full audit trail tomisable checklists. of any changes.

While onsite observation/ snags, health While many 19-year-old firms that have been growing and safety reports 60% annually for almost a decade would be wafting Conclusion can be quickly creatWhile US giants share value, revenue or profit as an essential part of Procore and Autodesk ed and documented their mainstage moment, Dalux is not in that game with the phone’s Construction Cloud camera, the system is look to dominate the smart enough to flow of data among know where in the site you are located - integrated into the Dalux ecosystem, so construction and subcontractor firms, time and floor. There are workflow tools to infrastructure models can be shared.

Dalux appears to be a European equivatrigger actions to those who need to resolve lent that is holding its own. However, remedial work. The reports are accessible FM - facilities management - is probably the Dalgaard brothers have managed to to project workers and issues clearly iden- another no brainer for following the design keep the firm accessible to its customers and construction data, into operations. It’s and build a unique relationship. tified on the latest drawings. quite refreshing to not have to deal with As I understand, firms pay fees based Field Basic is a free punch list tool that the branding bludgeon that is digital twin. on project size, as opposed to by number supports drawings and BIM models and FM is a web and mobile content manage- of users, meaning Dalux becomes the sinenables tasks, collaboration amongst ment system for 2D and 3D asset manage- gle source of truth for the construction ment, operations and maintenance. It com- data for all participants. defined groups, and sign-off. bines floorplans, mapping and modelling Dalux appears very support-centric, and Field Sitewalk enables the quick capture of based on location, aiding navigation. It it prioritises ongoing connection with a site using video from a helmet-mounted offers a helpdesk ticketing system, work developers and product champions in their 360 degree camera. The video frames make order generation, maintenance schedule customer base. It’s another reason why photographing the site effortless. These are and is a conduit for additional digitised 1,800 people would visit Copenhagen to automatically mapped in the Dalux system. documents, asset information, photos etc. meet up with what felt more like a bespoke Again, the smart application uses GPS outsourced software developer, than a firm Teams back in the office can use the system to see the current state of construction and to position the user in floorplans and can trying to meet next quarter’s targets. even compare the site against the BIM be used in conjunction with QR codes for ■ www.dalux.com

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Technology

Matterport goes Pro Reality capture began with costly terrestrial laser scanners, then advancements in photogrammetry-to-mesh significantly lowered the barrier to entry. Now, Matterport is bridging the gap by combining both technologies to deliver a scanner priced under $6,000, writes Martyn Day

L

aser scanners were first com- to deliver 3D environments of interior mercially available in the mid scans, combining HDR photogrammetry 1990s and they have been used with structured light sensors for depth across nearly all AEC disci- information.

Structured light sensors use a projecplines: civil engineering, surveying, architecture, heritage and quality con- tor and cameras to capture an object’s trol. The technology has moved from tri- 3D shape by analysing the deformation pods to backpacks, handheld to mount- of a projected infrared light pattern.

The most well-known applied on robot dogs. However, cation of this technology the one thing that has was from Microsoft with remained stubbornly fixed the Xbox One Kinect is the high cost.

Sensor, an add-on for its In 2012, Brian Mathews gaming console. who previously ran Structured light sensor Autodesk Labs, was made technology is significantly Autodesk VP of Reality different to LiDAR, which Capture, as Autodesk anticiuses time of flight of laser pated the ‘democratisation light to establish a cloud of of reality capture’. The clos3D points. est that revolution came to Matterport became very being was in 2016 when We’re trying to popular in high-end real Leica and Autodesk jointly identify the estate / estate agents and the launched the ultra-portable Leica BLK360 coupled with friction points company currently has 38 Autodesk Recap scanning of going from billion square feet of digital property currently under software on the iPad. design to the management in its platform.

At $15k the Leica BLK360 Matterport technology was half the price of most tedious task of other scanners and looked documenting a has been used in architecand construction to set to be the breakthrough space and then ture some degree, but not as a product that would bring the equally replacement for surveying. prices down. Faro soon folThe company shifted its lowed with a highly portable tedious task of but more accurate scanner at building up the business model to a subscription-based approach, around $20k but since then Revit model added support for 360 camthe appetite to drive costs Stephanie Lin, eras, and appeared to focus lower has evaporated. If anything, most new scanVP and GM - primarily on retail and real estate sectors. ning products have returned Operate at The subscription pivot to previous price points and Matterport really only made sense to the Leica BLK360 will now repeat volume users and not set you back around $20k. for occasional use. AEC is In 2016, Mathews told AEC Magazine that to really open-up the mar- very much project focussed and that ket, scanners would need to drop below seemed to be a mismatch.

The last two years have seen two sig$10k. That moment never really materinificant changes at Matterport. alised, until now.

The first was the release of the sub $6k Matterport was established in 2011 and brought out its first bespoke camera in Matterport Pro3, a LiDAR scanner and 2012. Over time the technology improved camera, which can cover 10-100m dis-

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tances with a precision of around +/20mm (at 10m).

The second is the company’s acquisition by the CoStar Group in April 2024 for approximately $1.6 billion. CoStar appears to have cottoned onto the Digital Twin wave and Matterport’s use of AI. The company has backing and resources to double down on its real estate market, as well as entertain addressing a pro market with advanced AI and ever more sophisticated scanners.

Leica BLK 360 G1 vs Matterport Pro3 At $6,000, the Matterport Pro3 costs $15,000 less than the latest Leica BLK360, so it’s not surprising that it can’t match the specifications of Leica’s compact laser scanner. See specs below.

• Matterport Pro3 – 100,000 points per second, spherical capture 20 seconds, +/- 20mm @10m.

• Leica BLK360 G1 – 680,000 points per second, spherical capture in 20 seconds, 4mm @ 10m.

Capture times are roughly the same, but the Leica BLK360 G1 has almost seven times the depth of density of points, and up to five times greater accuracy. Both machines capture very high-resolution spherical imagery and software can combine laser with photogrammetry.

However, the price can’t be ignored and as an opening LiDAR scanner the Matterport Pro3 is a good option. Of course, the entry-level specs may limit its suitability for applications that require higher levels of accuracy.

Understanding the market To find out more AEC Magazine talked with Stephanie Lin, VP and GM Operate at Matterport.

Lin is ‘one of us’. She started as a licensed architect in the state of New York and specialised in super tall skyscrapers. She worked for one year at www.AECmag.com

27/11/2024 16:47

SOM San Francisco, with the eminent Neil Katz and then did seven years at KPF in New York, London and Shanghai.

Post skyscrapers, Lin went in-house for eight years, to work with retail, specifically Michael Kors and Tory Burch. Lin understands the needs of retail and the pro level features that those in AEC design would love to have from low-cost laser scanning.

She explains Matterport’s offering, “With traditional laser scanning, you’re not just buying the hardware, you also have to train the operator in-house to use specialist software.

“Matterport does the registration and the stitching in the back end with our AI, which we’ve been using for 13 years now, so you can imagine, it’s quite well trained at this point.

“We’re trying to identify the friction points of going from design to the tedious task of documenting a space and then the equally tedious task of building up the Revit model.

“We kind of do full end-to-end for that beginning portion, which is get the quick scan, get the point clouds. You can even get a BIM file or a CAD file from us — remove the tedious day to day stuff and have your team go do everything else.”

Lin is convinced that the proprietary Matterport sauce is a major differentiator.

That’s the technology that overlays point cloud, mesh and high-resolution images in the back end when processing a file, as she explains, “We’re really addressing the full building lifecycle, because that’s actually where the expensive part is. It’s not digging the hole in the ground, it’s making that space,” she says.

“We are now very focused on two solutions for the industry, and that’s design / construction management, and then facilities management,” she adds. “We are used time and time again, especially in the documentation stage, for milestone captures and definitely for handover packages. But we need to own it, and we need to put it out that way. And so this is www.AECmag.com

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our big focus for the company.”

In terms of technology, Lin explains how Matterport now has automatic dimensions, the ability to merge complex spaces and to copy notes and annotations from one model to the next. “These are workflow challenges that have hindered people from adopting using Matterport technology on a more regular basis,” she says.

Matterport also has a team of service professional scanners, ‘the Uber on demand’ of scanning. If you want a scan, or don’t want to make the camera investment, it’s possible to have someone go and scan with the Matterport Pro3.

Matterport covers 77 countries or more.

That means, you could be based in New

York, and get something scanned in Cape Town by tomorrow.

Conclusion Matterport has taken on the mantle of the democratisation of reality capture. It has a usable device at a price point that is certainly in the right ballpark for mass adoption of LiDAR and photogrammetry.

Matterport seems very committed to going ‘Pro’, offering capabilities to AEC design firms and targeting the long tail of digital twin adoption. However, this will require ongoing evolution of the scanner suite, with more connectors to pro design tools and defined workflows.

■ www.matterport.com

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Software

DraftSight 2025 MCAD tool Solidworks once had issues working with DWG files, so it licensed a DWG clone and gave it away for free.

Over time, this product evolved into professional CAD tool, DraftSight. We look at the latest release

T

he defining CAD system of the 1980s was DOS-based AutoCAD and its proprietary DWG file format, which has dominated the market ever since.

However, the secrets of the DWG file format are now common knowledge and there are tens of drawing tools which all speak the same interchangeable language of lines, circles, arcs, and text etc.

Several tools are owned by long-standing CAD software companies, including Hexagon (BricsCAD), Gräbert (Ares) and Dassault Systèmes (DraftSight).

DraftSight offers a lot more than basic 2D CAD functionality. It supports LISP APIs, point clouds, drawing compare, and shortcuts. The software comes in Professional, Premium and Network (licence) versions.

Premium includes a sheet set manager, PDF import and batch printing, advanced 2D tools with 3D modelling, meshing and 2D parametric constraints. The Network version allows enterprise deployment with simultaneous usage and built in compliance, enabling cost savings.

The latest release - DraftSight 2025 provides a range of new and updated capabilities that cover all the drawing and output bases, such as PDF export settings, Batch and Print settings and a Lasso Selection. It offers both menu and ribbon bar interfaces simultaneously.

Below are some of the other highlights.

Dimensioning: a new auto dimension feature makes complex dimensioning tasks simple with minimal input. In addition to manual dimensioning, DraftSight’s Smart Dimensioning tools figure out the best dimension type based on the entity selected.

Table management: Tabular information can now organise data better, automating formulas, adding consistent formatting, grips for manipulating tables, and support for breaks and block insertion.

File formats: A new STEP file import feature integrates externally created 3D models into 2D drawings. The IMPORTSTEP command can bring in complex mechanical parts. The new EXPORTDGN command lets users convert DWG drawings to Bentley Systems’ DGN format to aid those working in infrastructure.

Flatten: For those with drawings that have entities spread over the Z depth, the flatten command brings everything down to zero. This enables the easy clean-up of files which may have artifacts in 3D space.

Block management: The new Block Structure Palette helps designers see

nested blocks and complex hierarchies more clearly (preview, isolate). The palette also organises design elements better and reduces time spent looking through complex block relationships.

Visual style options: The Visual Style Manager offers multiple viewing choices wireframe and realistic rendering, conceptual and sketch appearances, X-ray visualisation. Using custom presentation styles, users can select how and which entities appear within a single block. There is also more visual control with a fill visibility for various entities including polylines, solids, traces, hatches, and gradients.

Conclusion DraftSight 2025 provides practical workflow improvements with overall better performance on loading, views and stability with big drawings. There are also usable upgrades to file management, block structure control, and dimensioning systems, together with expanded file support with STEP (for MCAD models) and DGN export (useful for AEC).

As DS licenses its core technology from Gräbert, it also has access to Gräbert evolving auto drawing capabilities, which were demonstrated at NXT DEV (www.tinyurl.com/Grabert-NXT).

In the next release of DraftSight, if not sooner, we imagine we will see some particularly useful assistance in batch autogenerating drawings from MCAD and BIM models, as DS turns its focus to additionally cater more for AEC users.

■ www.draftsight.com

Why does AutoCAD still cost so much?

With software budgets being squeezed, many AEC firms are questioning why AutoCAD still costs so much — especially when it’s no longer cutting-edge technology.

At time of writing, AutoCAD costs £1,986 / year. Meanwhile, BricsCAD Pro (Mac or PC) is £484 / year, DraftSight Professional £249 / year, DraftSight Premium (Mac or PC) £499

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/ year, and Gräbert Ares Commander (web, mobile or desktop) £300 / year.

Of course, there’s also the cut-down version – AutoCAD LT – which costs £486 per year. But AutoCAD LT has limited API, 3D, automation and collaboration capabilities.

On a pure like for like basis, at today’s prices it’s possible to get four seats of DWG equivalent drafting to

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one full AutoCAD seat. That even goes up to eight to one on yearly subscriptions. Some vendors also offer the design director’s favourite network licensing – where users can share a pool of licences.

Of course, it’s important to point out that users of Autodesk’s Suite / Collection bundles for vertical markets deliver better value, where

AutoCAD is one of many commonly used Autodesk industry tools (Revit, Navisworks, 3ds Max).

However, the cost of these bundles will be going up in the near future and there will an end to the 2 for 1 perpetual to subscription 8-year deal.

All of this is giving AEC firms plenty of food for thought, as they re-evaluate their software estates.

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27/11/2024 16:49

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