For the past decade, our purpose at Obvious Ventures has been to support entrepreneurs building disruptive solutions to humanity’s biggest challenges across three pillars: Planetary Health, Human Health, and Economic Health. We describe this as world positive venture capital, and we’re proud of the positive impact our portfolio companies have made over the past ten years, from pioneering plant-based meat to driving decarbonization.
As we look ahead to the next decade, we’ve identified artificial intelligence as a game-changing technology that will accelerate solutions across the trilliondollar industries we invest in. Specifically, we’re focused on startups building AI trained on scientific data from areas like chemistry and biology to solve previously unsolvable problems. We call this approach “generative science.”
As optimistic as we are about modern AI, we are also mindful that evolving technology must operate within the bounds of scientific rigor and ethical standards. Issues of data privacy, algorithmic bias, and the potential misuse of AI-generated discoveries demand a vigilant and proactive approach. We see it as our responsibility to help build the guardrails that ensure generative science serves the greater good.
In this year’s report, we highlight some of our investments leading this new AI frontier. And we share our vision of the future we want to see. As you read about large science models driving discoveries in areas like messenger RNA (mRNA) vaccines and geothermal energy, we invite you to dream with us. We believe we’re just at the starting line of a new wave of innovation, with generative science delivering forward leaps across healthcare, drug discovery, battery chemistry, financial wellness, and more.
In partnership with our portfolio founders and our limited partners, we are more excited than ever about our world positive purpose to build and scale solutions that move humanity forward.
James Joaquin Co-founder & Managing Director
Vishal Vasishth Co-founder & Managing Director
Andrew Beebe Managing Director
Our New Impact Reporting Framework
Each year, we publish this report to showcase the amazing impact our portfolio companies are making on the world. Our company profiles give you an inside look, with bespoke metrics for each company.
This year, we are adding a new reporting framework that is anchored around the United Nations Sustainable Development Goals (SDGs).
Born at the UN Conference on Sustainable Development in Rio de Janeiro in 2012, the SDGs have become a widely accepted framework for investment portfolio impact.
In this year’s edition, we provide a high-level summary of our impact across our entire portfolio, with detailed SDG reporting within each of our three pillars and full portfolio details at the end of the report.
Generative Science
Our Contrarian View of AI
By James Joaquin
In 2017, eight researchers at Google published a groundbreaking paper called “Attention Is All You Need” that laid the foundation for transformer-based artificial intelligence, or what we now know as generative AI. The first use of the technology was to generate media like text, images, and video.
Generative media has been a revolution. But the next wave of generative AI—generative science—will be far more transformative to the human race and usher in the next wave of trillion-dollar companies. While most venture dollars are chasing large language models (LLMs) for enterprise productivity, Obvious is funding large science models trained on chemistry, physics, and biology to generate new scientific breakthroughs in decarbonization, biotech, materials science, and robotics.
The idea behind generative science is simple: train AI on our knowledge of the physical sciences like chemistry and biology and then utilize that AI to generate scientific breakthroughs that discover new materials, new drugs, and new vaccines. Not only is generative science (or GenSci) already enabling breakthroughs—
it’s also rewiring every field of science, from physics to chemistry to biology, with enormous potential for the future of our species and our planet.
We believe generative science will emerge as humanity’s greatest invention because it is, for the first time, an invention that can invent.
Generative media has delivered us a printing press that can write its own words, but generative science will deliver a more consequential lab bench that can create its own novel arrangements of atoms. Those new chemicals and molecules will help solve humanity’s toughest challenges, from nuclear fusion to a cure for cancer, and open entirely new avenues of exploration that we’ve long considered beyond our reach or have never considered at all.
4. Generative Science
The era of AI for breakthrough science
3. Generative AI
The era of AI for text, images, and video
2. Deep Learning
The era of neural networks
1. Machine Learning
The era of big data
The four major eras of AI.
Solving the unsolvable
Generative science can take on bigger quests with incredible speed. One of the world’s biggest obstacles over the next decade will be creating enormous new supplies of clean energy to power advances in AI, decarbonization, and the electrification of nearly every sector. By some estimates, we need triple or quadruple our current baseload power.
Nuclear fusion is our best shot at unlimited clean energy, but it remains out of reach. Generative science is already enabling major progress much faster than human researchers possibly could. Using AI-powered learning systems, researchers in Switzerland have discovered how to control the extremely hot hydrogen plasma that collides in powerful fusion reactions, a crucial step that brings us closer than ever to a world-changing scientific breakthrough.
On another front, geothermal energy—long an expensive and hard-to-reach source of power—is also getting a major boost from generative science. The Utah-based geothermal company Zanskar has shown it can outperform the best human geologists in site exploration by applying AI to analyze rich geologic data to identify new energy sources and novel ways to reach them.
With generative science, this old method is going extinct. Today’s generative science models bring unprecedented capabilities in hypothesis generation, experimentation, and data analysis. Future iterations will autonomously generate vast quantities of data, simulate complex phenomena, and explore widespread possibilities across massive search spaces. These systems will detect patterns, anomalies, and correlations in data that human researchers might otherwise never discover.
Biotechnology and healthcare are the richest spaces to witness the new scientific method in action. We already saw a major biotechnology revolution in 2020 when scientists used messenger RNA (mRNA) to develop Covid vaccines in record time. Messenger RNA can theoretically address almost any disease, but there are an impossibly large number of possible mRNA sequences (even a relatively simple protein like the spike protein in the Covid vaccines can be coded in as many as 2.4 × 10632 potential mRNA arrangements). But well-trained generative science models can search across multidimensional data spaces and surface relevant pathways at unprecedented speed.
Obvious portfolio company Inceptive is leading the RNA revolution. Inceptive was founded in 2021 by Jakob Uszkoreit, one of the
ATOMS to BITS
rapid sequencing, etc.
SPECIALIZED AI MODELS
BITS to ATOMS chemical and biological synthesis
CUSTOM ASSAY TESTING, SAFETY, AND VALIDATION
At the simplest level, generative science works as an information flywheel (circular from top left): 1. Biological material (atoms) is converted into training data (bits). 2. Large multipoint attention prediction models find patterns and make predictions. 3. Bits are converted back to atoms for testing and validation. 4. Findings are fed back into steps 1 and 2 to clarify the next round and make the AI smarter.
Bridging these physical components with the digital world requires infrastructure that can convert chemical and biological matter (atoms) into data-rich information (bits) that can be processed and analyzed by computers. It must also act in reverse. Once the AI predicts a possible breakthrough—such as an mRNA molecule or a protein sequence that can instruct cells to fight colorectal cancer—the data finding (expressed in bits) must be converted back into biological material (atoms) that can be tested, validated, and eventually deployed with high confidence of safety and efficacy in cancer patients.
New hardware and software needed for the advanced synthesis of chemicals and biological materials will be an exciting area of progress (and venture investment) in the years ahead.
What’s more, we know from early iterations of generative science that the quality of scientific output is only as good as the quality of scientific input. The best results are based on accurate and wellcurated data and should be verifiable and reproducible, particularly when applied in sensitive areas like human biology. Noisy data or so-called data leakages not only produce unreliable and unreproducible results. They also undermine investment and trust in other areas of generative science that can transform industries and save lives.
AI science in action
The centerpiece of generative science is combining AI-powered software with hardware that can accelerate the pace of experimentation and analysis. In 2009, researchers did this for the first time with a robot called Adam that predicted gaps in the known genome of baker’s yeast. Now we have the tools to supercharge that process.
The next iterations will autonomously conduct the entire scientific process. Robotics systems will use AI to postulate hypotheses, conduct experiments with physical materials, analyze experimental data, and then use relevant learnings to formulate new hypotheses.
This robotic cycle doesn’t replace human creativity, but it does minimize human error. The same way developer tools empowered software engineers with new features and functionality, generative science will empower lab scientists to think expansively without the time-consuming and laborious work of measuring, moving, and observing materials.
AI-powered robotics will be especially powerful in drug discovery. TechBio company Recursion has developed an operating system that can perform millions of automated experiments every week to explore how biological systems and chemistry interact. Other companies are building platforms designed to autonomously discover synthetic chemicals and new materials. Accelerated lab research will yield broader possibilities in every field of science.
Building crucial guardrails
Humans have always been the central conductors of science, and they will continue to be. While generative science can enhance our capabilities and speed up discovery, human oversight is key to keeping systems running safely and ethically. Trained scientists must design the experiments, interpret the results, and ensure that the technology can be accessed only by those who know how to manage it and protect it. Such powerful technology poses the classic dual-use dilemma. Generative science that improves life on Earth could be co-opted in the wrong human hands. The same biological printer that makes it possible to print food-grade plastic with no petroleum could also be used to print a bacteria 10 times more lethal than E. coli. The same chemical synthesizing engine that makes the compound ingredients for a breakthrough battery could be directed to build devastating bombs and explosives.
That’s why for generative science to be world positive, it must work on the broad E-T-H-I-C-S checklist, included in this report, that I developed with my colleagues at Obvious. The systems behind AI-powered science must be explainable and transparent to build trust in how systems process complex data to arrive at complex conclusions. Their work must be human-centered and inclusive to minimize bias and blinders that could disadvantage broad communities, and they must promote civility and progress across the broader world. Crucially, these systems must be sustainable in how they consume energy and resources. While governments scramble to design regulatory frameworks for AI, we encourage founders to act now, staff their own red teams, and build safeguards and guardrails into their AI systems.
Bright minds needed
We believe generative science will create an exponential acceleration in scientific breakthroughs. The innovative startups that drive these breakthroughs will need cross-disciplinary teams that live at the intersection of AI and some of the world’s largest industries. We’ve highlighted some exciting examples of AI in climate, healthcare, and robotics. That’s just the beginning. We’re searching for generative science startups also reimagining future growth industries like robotics and advanced materials.
Obvious is investing at these frontier intersections, and we’re convinced that the crossroads of AI and biology will spur advances that transform planetary and human health. Overlaps of climate and AI will yield new solutions to accelerate renewable energy and mitigate climate change. Like any exponential technology, generative science will also bring new risks. We’ll need ethical, responsible companies to shepherd this technology in ways that dramatically improve human and planetary health.
In 1929, T.S. Eliot famously wrote, “Genuine poetry can communicate before it is understood.” Generative science is on a trajectory to become the greatest, most poetic creation of our species, communicating scientific breakthroughs that humans will subsequently test, validate, explain, and understand. The marriage of human ingenuity with generative AI represents a profound symbiosis, propelling us toward a future where the limits of what we can imagine and achieve in science are continually challenged and, to an increasing degree, surpassed.
Generative Science
The richest scientific breakthroughs are likely to come where trillion-dollar industries intersect with generative science.
The Essential Generative AI E-T-H-I-C-S Checklist
By Kahini Shah
Generative AI holds immense potential to revolutionize industries, from healthcare to energy to financial markets. Its ability to create, predict, and innovate opens up possibilities humans have only dreamed of—or have never considered at all.
However, if generative AI is misused or developed irresponsibly, it could cause significant harm. Unchecked, it could perpetuate biases, infringe on privacy, spread misinformation, and create deadly substances. Companies developing generative AI must navigate the fine line between innovation and exploitation.
In this spirit of optimistic vigilance, we developed an essential guide for all generative AI applications. This checklist aims to help leaders and companies harness AI’s transformative potential while safeguarding against its risks, ensuring that this powerful technology serves humanity positively and responsibly.
Generative AI must be …
01 Explainable
Are significant decisions made by your AI explainable? Can humans appeal, modify, and override those decisions?
Explainability in deep learning was already difficult, and it’s even harder now with larger models. However, explainability is crucial to understanding how AI arrives at simple conclusions from complex data. For example, AI can use alternative data sources to make the credit underwriting process faster and fairer to marginalized economic groups, but it’s important to understand the models and benchmarks to verify that decisions are made correctly and fairly.
Frameworks, such as Stanford HELM (Holistic Evaluation of Language Models), can help benchmark AI products and encourage greater transparency in training data curation and model development processes. Companies such as Arize AI allow you to monitor, troubleshoot, and evaluate your models, while Patronus AI helps detect large language model (LLM) mistakes.
04 Inclusive
Have you identified and removed bias from your AI systems? Are you testing your AI so it does not discriminate?
AI models are only as good as the data they are trained on. If we train a model based only on mammals, we cannot ask the model about snakes. In the same way, we must ensure that data for sensitive use cases, like clinical medical decision support, is inclusive of racial, ethnic, and economic groups so we can have confidence that outputs are free of bias.
Not every user—or in this example, every doctor—needs to be familiar with full datasets. But regulators and administrators can rely on infrastructure tools that help users understand datasets, such as those from Nomic, or ones that help curate and catalog data, like those from Datalogy.
02 Transparent
Are your development, training datasets, and deployment processes transparent?
We’ve already seen the importance of transparent data in image and video generators. We don’t understand how many of these large models are trained and what datasets they draw from. Many image models have been trained on the LAION dataset, which was found to contain explicit pictures of children. Authors, artists, and media companies have also raised copyright issues over the unauthorized use of their work.
Transparency can come in many forms. It’s important to understand the data a model is trained on, the techniques used, and how the model is weighted. Some systems, such as OpenAI’s, are closed. We are excited about the rise of open-source models like Meta Llama-3 and Mistral AI, which are taking positive steps, such as disclosing model weights.
03 Human-Centric
Is your AI designed to meet human values and needs? Does it prioritize the well-being of people?
We can already see the possibility of deploying AI therapists or AI financial advisers. But when people interact with these systems, they need to be able to trust that the AI is working in their best interest. That means outputs must be not only factual, but also compliant, legal, and safe.
Putting the well-being of humans front and center can start with smart government regulations, such as the European Union’s AI Act, which prohibits systems that are subliminal, manipulative, or deceptive. It’s also an opportunity for companies to design responsible safeguards. Potential solutions exist in the work of early-stage companies like Guardrails AI and Norm Ai, which screen AI outputs for compliance, legal, and ethical violations.
05 Civil
Does your AI ensure civil communication? Does it drive conversation that is factually correct?
We’ve seen ways AI can be civically harmful, such as when fake AI robocalls of President Biden attempted to suppress the vote or when fake images of nude celebrities are viewed by millions. Deceptions can have widespread consequences. Consumers lose nearly $9 billion every year in financial fraud, which experts expect AI to make worse.
We need solutions to help detect and protect users from deceptions big and small, particularly the ones that can cause widespread social disruption. Digital watermarking is another way companies can identify and label how content is made. And techniques such as retrievalaugmented generation can help contextualize information and reduce hallucinations, a feature innate to LLMs.
06 Sustainable
What is the environmental impact of your AI? Is there a path to make your AI data center carbon neutral?
Every query to an AI model comes with an environmental cost. Creating one image with generative AI takes as much energy as charging your iPhone or driving your car 4 miles.
Companies are looking at new ways to power their data centers. Our portfolio company Zanskar is working to harness geothermal energy. Making an AI data center carbon neutral will require continuous efforts toward renewable energy, sustainable cooling systems and carbon offsetting, and monitoring and reporting emissions.
Planetary Health
Decarbonization is the solution to planetary health. We back founders who are combining traditional industries with new technologies that better our world. We believe in a future where everything is electrified, energy is renewable, manufacturing and workplaces are safer, and agriculture is resilient.
A New World Built Around Clean Energy
By Andrew Beebe
As the urgency to address climate change intensifies, global energy is undergoing a seismic shift. The transition to clean energy is not only here—it’s accelerating. Innovations in generative science are driving profound changes in renewable generation, transmission technologies, and data-driven user incentives that will ripple across industries.
The numbers tell the story. The International Energy Agency projected that investments in cleantech and infrastructure will hit $2 trillion in 2024, roughly double the investment in fossil fuels. The U.S. slice of this global sum is small—just 15%—but is growing sharply thanks to major incentives in the Infrastructure Investment and Jobs Act and the Inflation Reduction Act.
We are especially enthused about geothermal energy. Despite renewables like wind and solar reaching relatively large scale and low cost, neither has proven capable of providing the comparable baseload capacity of coal, oil, and gas. New leaps in geothermal energy are unlocking vast new energy deposits in the earth’s crust, and generative AI technologies are making them more accessible than ever before.
Here’s a glimpse of the future we envision:
01
Clean energy will finally leap past fossil fuels.
The era of fossil fuels dominating the energy sector is drawing to a close. Solar, wind, geothermal, and hydropower are poised to overtake fossil fuels in baseload capacity, global efficiency, and declining costs. New technologies are unlocking vast new deposits of clean energy and powering leaps in traditionally slow research quests like nuclear fusion.
02
03
Carbon removal will hit overdrive.
Technologies for carbon capture and sequestration are rapidly advancing. Innovations in direct air capture and bioenergy with carbon capture and storage are scaling up. Both are making it possible to remove and store carbon dioxide far more efficiently and for the world to meet broad climate targets.
04
Agriculture will transform from top to bottom.
Farming is undergoing a clean energy revolution. Renewable energypowered machinery and precision data-driven farming techniques are breathing sustainability into a historically carbon-heavy industry. Innovations in vertical farming and lab-grown foods are also emerging, reducing the carbon footprint of food production and increasing food security.
05 Advances in battery chemistry will rewire industries.
Breakthroughs in battery technology are transforming the landscape of energy storage and consumption. New chemistries like solid-state lithium and synthetic silicon batteries promise greater energy density, faster charging times, and longer lifespans. These advancements are crucial for the scalability of distributed renewable energy, enabling industries to reduce their dependence on the grid significantly.
AI will take the guesswork out of risk analysis.
Advanced algorithms and machine learning models can predict equipment failures, optimize maintenance schedules, and improve energy efficiency. By leveraging AI, businesses will be able to make more informed decisions, enhancing the reliability and resilience of renewable energy systems and reducing operational uncertainties.
Meeting a Surge in Demand With Clean Energy
By Anku Madan
We have entered an era of explosive energy demand. This growing need, driven by electric vehicles, the electrification of industries, and the proliferation of data centers to support AI, calls for an urgent transformation in how we generate, transmit, and use power.
The numbers are eye-popping. Some state utilities project their energy needs will double or even triple in the next decade. According to the International Energy Agency, global energy demand in 2025 is projected to grow 50% faster than in prior years, and demand from data centers, AI, and cryptocurrency is expected to double by 2026. This surge highlights the pressing need for innovative solutions.
And it comes at an extremely challenging time. Climate change is transforming the world even faster than models predicted. Extreme weather, more intense natural disasters, and the breakdown of ocean currents and polar ice are causing dramatic changes to our planet and our way of life. The world needs to stay below 2 degrees Celsius of warming and, ideally, below 1.5 degrees, if it’s not too late.
To meet our energy needs in a way that drives worldwide decarbonization, we need a comprehensive overhaul in three critical areas: generation, transmission, and usage.
01 02
Generation
On the generation front, our current energy infrastructure is not equipped to handle this demand surge in a way that aligns with U.S. and global climate goals. Reliable baseload power has traditionally come from fossil fuels. As we decarbonize, existing renewables can’t make up the difference. Solar and wind, while dramatically cheaper and more accessible, are intermittent sources that can’t meet 24/7 baseload demand. They are also mature industries that have moved into the realm of project financing and infrastructure funding.
This is where venture capital is crucial. Leveraging smaller amounts of capital can drive significant growth and innovation in new baseload generation. The potential is largest in four promising areas:
Nuclear fission
Existing fission technology is experiencing a renaissance with the advent of small modular reactors. These reactors offer a promising avenue for accessible and reliable power to data centers, military bases, remote locations, and industrial facilities. Despite their heavy regulations and high installation costs, Obvious sees opportunity in this space.
Nuclear fusion
Fusion, often hailed as the holy grail of baseload power, presents a longer-term solution. Companies like Helion Energy, Zap Energy, Avalanche, and Thea Energy are leading this exciting field. But fusion is not expected to be a viable option for another seven to 20 years, and even promising breakthroughs still require major investment and fundamental de-risking.
Hydropower
Hydropower has been the backbone of low-carbon electricity for decades. But hydropower also faces high capital expenditure costs and a saturated market with limited opportunities for developing new capacity.
Geothermal
Energy derived from heat in the earth’s crust offers the lowest-cost option currently available. Geothermal is getting major boosts from generative AI, including from our portfolio company Zanskar (page 24), which deploys advanced computing to locate rich geothermal resources faster and more efficiently than ever before. AI leaps in geothermal are projected to cut the cost of new geothermal in half, from $80 per megawatt-hour to as low as $40 by 2040.
Transmission
Overhauling our transmission infrastructure is the first crucial step to accommodating these new leaps in generation. Our existing grid infrastructure was designed for centralized power sources, and the transition to distributed sources like rooftop solar, smallscale installations, and home batteries requires a fundamental shift. We can start with transitioning from static line ratings to dynamic line ratings, which can enhance transmission lines’ efficiency and capacity. Companies like Splight, VEIR, and LineVision are pioneering advancements in transmission technology, including using superconducting materials to increase line carrying capacity.
03
Usage
The third piece of the puzzle is industrial power use. The industries that use the most energy—agriculture, chemicals, and transportation—will drive society to net zero by renovating, retrofitting, and reinventing themselves. This requires a collaborative effort between industry and government, leveraging policy incentives to drive the transition. Early-stage grants and loan guarantees are crucial to accelerate the development of better and cheaper technologies.
The good news is that we can meet these challenges. For the past 150 years, we’ve proven through every energy bottleneck and growth spurt that innovation can overcome even the most daunting obstacles. Today’s moment strikes some as intimidating, even perilous. However, looking at it another way, the transition to a decarbonized future has never been more promising. Obvious is excited to accelerate the innovations that will shape a sustainable energy landscape long into the future.
Planetary Health and the Sustainable Development Goals
From AI Fleet to Zanskar, the Planetary Health companies we invest in are making great strides toward five Sustainable Development Goals. These goals include taking urgent action to combat climate change and its impacts (Halcyon and Arbor, among others), ensuring access to affordable, sustainable, clean energy (Forum Mobility and Synop), making cities safe and sustainable (Plant Prefab and Lightship), ensuring sustainable consumption and production patterns (Enervee and others), and building resilient infrastructure and sustainable industrialization (Canvas, Dexterity, and more).
Halcyon A Data-Driven Approach to Decarbonization
Climate change is the greatest challenge of our time. Extreme weather and a warming planet affect every industry and sector, threatening our food, energy, infrastructure, and life as we know it.
The U.S. target is to reduce greenhouse gases by 50 % by 2030.
Decarbonization—the process of transitioning from fossil fuels to renewable energy—is one of the most powerful ways to address climate change. And speed matters. That’s where Halcyon comes in.
Halcyon is building an AI-assisted search and information platform to accelerate decarbonization. The International Energy Agency estimates that the world needs $4 trillion of clean energy investment by 2030 to reach net-zero greenhouse gas emissions by mid-century. In the U.S., the target is to reduce greenhouse gas emissions by 50%–52% by 2030 and to fully decarbonize our power sector by 2035.
Reaching these goals starts with data and information. Data reveals where to find the risks and opportunities in new renewable energy development. It prepares regions and utility providers for energy needs and forecasts future costs. With better access to data, energy companies won’t see clean energy as a hope or a gamble but as a strategic path to financial, operational, and market success.
It’s not just energy companies that will benefit from Halcyon’s platform. Every company on the planet has an interest in decarbonization and minimizing climate risk. Large tech companies want to ensure their data centers have enough power to grow for decades. Agriculture companies need to forecast future crop yields. Financial institutions need to protect their branches and servers from extreme weather. All of them want to know how to stay ahead of the competition and the changing climate, and every strategic decision they make is rooted in access to information.
In the same way that every company has become an “internet company,” every company will soon become a “climate company.” Running a successful company will require managing climate risks and finding opportunities to expand and grow sustainably. Platforms like Halcyon will help companies navigate this challenge and uncover new opportunities that are hidden in plain sight.
Zanskar Going Deep on Geothermal
Recent technological leaps have given us many reasons to be optimistic about the future. Generative AI is opening a new era of scientific discoveries, crypto is defining new processing paths, and the electrification of almost every sector is fueling the world’s decarbonization.
We will need at least 3x as much energy by 2040
100 gigawatts of potential U.S. geothermal electric capacity
But here’s the catch: All of these initiatives require massive amounts of energy. According to an estimate from U.S. energy utilities, we will need three times as much energy generation by 2040 as we have today—and possibly much more.
Aging fossil fuel plants can’t meet this soaring demand, nor can renewables like wind and solar that have already tapped most of the accessible land. Nuclear fission is expensive to build and maintain, and nuclear fusion, while getting closer to reality, is still out of reach.
Thankfully, there’s a solution under our feet: geothermal energy. According to the U.S. Department of Energy, there may be over 100 gigawatts of geothermal electric capacity in the continental U.S., accounting for nearly 10% of our current electricity capacity. Geothermal—extracting thermal energy from the earth’s crust— has traditionally been limited in two key ways: It’s hard to find and costly to develop.
Zanskar is building a powerful AI platform that reduces these barriers, redefining how and where we find enormous new supplies of power. The company uses AI to analyze temperature, gravity, geology, and geophysics datasets to identify new sources of commercial geothermal and to guide decisions about where and how to drill. In the past few years, Zanskar’s technology has dramatically accelerated the speed of data analysis and exploration decisions, finding more high-potential sites in the previous 12 months than the industry did in the past decade. Backtested demonstrations show they outperform the best human geologists in complex and high-cost decision-making situations where geothermal projects typically fail. New sites paired with better decision-making will unlock a new wave of geothermal development.
Geothermal is seeing a massive expansion of cost-cutting technologies, from fracking to deep-well drilling. These helpful technologies will be combined with Zanskar’s discovery platform to usher in a new era of low-cost, accessible, and fast development of baseload resources. The Zanskar team is already demonstrating how breathing new life into an old industry can boost baseload power while also decarbonizing our world.
Diamond Foundry
Adding Bling to Microprocessing
Generative AI is leading to a new era of scientific discoveries. And as engineers add more functions into the microchips that power this technology, more energy is required. The amount of computing power needed to power new AI models from one generation to the next is increasing tenfold on average.
Diamond Foundry’s diamond wafers are less than 3 millimeters thick.
Synop
Leading the Charge
Transforming the economy to run on clean electricity is a cornerstone of the U.S. government’s plan to address climate change by reducing emissions to net zero by 2050. Gagan Dhillon and Andrew Blejde co-founded Synop in 2021 to help with the transition.
Synop Excels at Interoperability
Any Utility
Electricity Suppliers / DSO / TSO / Aggregators
“The ultimate goal is for us to be gatekeepers of any energy source that can create a more resilient grid, scale electrification, and lead to a cleaner, more decarbonized world,” explains Dhillon.
The North American electrical grid is facing increasing challenges in providing reliable electricity, especially in the face of extreme weather and demand spikes. Backup power storage has become essential during weather events like hurricanes, cold snaps, and heat waves. It’s crucial that the grid remains dependable to keep vital services, like nursing homes, hospitals, and schools, running smoothly.
Synop is addressing this issue by helping pioneer a program where electric school buses discharge energy from their batteries back to the grid. Over the past three summers, Synop’s charging and energy management software helped electric school buses participate in vehicle-to-grid programs. The results showed that one bus discharged 10.78 megawatt-hours (MWh) to the grid over 158 hours, generating $23,500 for the school district. The program is now operating in five states.
Another way Synop is scaling electrification is with the release of their new product SynopLink. This product was designed to improve on-site charging operations at electric vehicle (EV) fleet charging stations.
As more commercial trucking companies make the switch to EVs, many have been building on-site distributed energy resources (DERs)—such as power generators, large-scale batteries, and solar arrays—to meet the enormous electricity demands of these large, heavy-duty EVs.
Any Vehicle
Any class 1-8 vehicle
Any Charger
AC / DC / Bidirectional
These solutions are prone to faults and power outages if generators and batteries aren’t functioning optimally at all times. SynopLink collects, analyzes, contextualizes, and communicates data from each on-site DER device in real time. With this information, it adjusts the amount of power that EVs can pull from the microgrid, preventing vehicles from drawing more power than is currently available in on-site batteries and enabling a more sustainable commercial transport sector.
+$23,500
One bus discharged 10.78 MWh to the grid over 158 hours, generating $23,500 for the school district.
Arbor
Flipping the Switch on Home Decarbonization
In the fight against climate change, we need to decarbonize everything, including our homes. Residential energy use accounts for 20% of greenhouse gas emissions in the U.S., equivalent to the total emissions from the UK, France, and Italy combined.
America’s desire to decarbonize at a residential level is growing— $9 billion in energy rebates was earmarked just for this in President Biden’s 2022 climate bill, plus an uncapped amount of tax credits for climate technologies like solar, battery storage, and heat pumps— yet it’s often confusing for the average consumer.
Arbor is an innovative digital platform that streamlines home energy management. Today, the platform helps consumers save on their electricity bills without changing their power reliability or billing process. With a few simple clicks, users can connect their utility account to Arbor, and the company will switch them to a more affordable electricity supply rate so they can start saving money on their next electric bill.
Arbor’s approach to consumer engagement sets them apart in the deregulated energy market. By tapping into the majority of consumers who are not typically interested in switching providers,
or don’t even know it’s an option, Arbor has expanded the total addressable market. Seventy-seven percent of consumers today are worried about energy costs, but most don’t know anything about rates and supply shopping. By aggregating homeowners on their platform, Arbor is also able to secure exclusively low rates in energy markets and provide these rates directly to customers, without them having to do a thing.
Over the past 18 months, over 40,000 users have signed up for Arbor and gotten a better rate. More than $3 million has already been collectively saved for Arbor customers, with an average of $192 annual savings per customer.
Residential
energy use accounts for 20% of greenhouse gas emissions in the U.S., equivalent to the total emissions from the UK, France, and Italy combined.
Human Health
We make investments that lead to healthier lives, from wellness products and healthy food to AI-powered drug discovery.
We back tech-enabled research and innovation of healthcare delivery, outcomes, and costs.
By strengthening health systems, we anticipate a future of proactive health, better care, and more consumer choice.
Predictions
Machines Will Help Heal Healthcare
By Vishal Vasishth
Every few years, we hear about a medical advancement that breaks a barrier. Discoveries like Ozempic for diabetes and obesity and experimental cell therapies to cure lupus are hailed as discrete advances.
The next major wave of healthcare innovation, powered by generative science, will be more continuous. Machine intelligence will produce breakthroughs in methods and technologies that will enhance the entire healthcare value chain from bench to bedside.
Here are five bold changes we see on the horizon:
03
Clinical care will get a boost from AI assistants.
Clinical specialists at all levels—doctors, nurses, and staff—will carry a “clinical brain” to enhance and supplement their knowledge and experience. This “brain” will be trained on a vast quantity of textbooks, peer-reviewed papers, and the latest research, and it will democratize access to accurate real-time medical information. This tool will enable better decision-making for patients and providers, reducing unnecessary burdens and human errors.
01
AI will revolutionize drug discovery.
AI-enabled advancements are already revolutionizing drug discovery. Models like AlphaFold 3 and OpenCRISPR are solving significant biological problems, such as designing novel geneediting enzymes. AI-powered in silico methods improve hypothesis generation, target identification, and lead optimization. Obvious investments in Inceptive (page 40) and GenHealth (page 42) are delivering early evidence that machine intelligence can reduce the cost and time of biological research, accelerating the journey from initial discovery to early development.
02
Precision medicine will become truly personalized.
Precision medicine stands to benefit enormously from multimodal AI, which can process diverse data to deliver personalized treatment plans. Oncology is likely to see the first applications, with AI leveraging radiology scans, pathology slides, molecular diagnostic assays, and patient records. These models may detect cancer earlier, predict recurrence more accurately, and tailor individualized treatment plans with unprecedented effectiveness.
04
Robotic automation will lead surgical suites.
Tele-operated robotic surgery is already a reality, and the next frontier is autonomous robotic surgery, which will enhance precision and efficiency in medical procedures. These advancements will lead to fewer errors, quicker recovery times, and more consistent surgical outcomes.
05
AI will streamline healthcare administration.
Healthcare administration will see significant changes, with AI agents taking over core workflows. Tasks such as appointment scheduling, prior authorization, electronic medical record review, medical coding, and care coordination will be managed by AI, reducing administrative costs and allowing healthcare providers to focus more on patient care. This shift will streamline operations and improve the overall efficiency of healthcare delivery.
Essay How to Solve a Trillion-Dollar Healthcare Problem
The growth in healthcare administration is staggering. According to data from the Bureau of Labor Statistics, between 1970 and 2015, the number of clinicians grew 150% while healthcare administrator jobs grew over 3,000%. This especially hurts independent and small-office providers, where inflated administrator-to-physician ratios cause financial stress, budget cuts, and compromises in care delivery.
It’s a trillion-dollar problem. And we’re finally at the moment to solve it with a powerful system of AI-powered assistants known as agentic
Next-generation AI automation
AI agents are changing the old paradigm of enterprise automation. Unlike legacy robotic process automation, which can be used only in highly defined, rigid, high-volume use cases, AI agents are intelligent, flexible, and autonomous problem solvers that are becoming increasingly robust. The key advance is in AI agents’ ability to solve small goals in service of a larger overarching goal.
Imagine a patient with a skin issue trying to book their first appointment with a dermatology specialist. An AI agent will split up the overarching goal—booking the appointment—into smaller goals: (1) check the patient’s referral, (2) flag missing information, (3) confirm suitable times, (4) send a reminder before the day of the appointment. AI agents can determine when a subgoal has been achieved and move to the next step. And they can work across modalities, like reading and writing text as well as performing phone calls in a human voice.
This technology will smooth every stage of healthcare delivery. It will supercharge a clinic’s front office capabilities and facilitate better communication with patients. It will scrutinize patients’ charts to avoid costly errors. And it will verify medical codes and coverage policies to quickly reconcile payments between patients, providers, and insurers.
Money saved through AI-driven administrative efficiency will be widely distributed. Doctors and clinicians will find reductions in overhead, making them more revenue to a point. The extra savings will mean more resources for prevention and care, allowing them to allocate more time and resources to patient care and innovative treatments. This could lead to a shift where medical professionals focus more on quality care than administrative tasks.
Crucial guardrails and industry stability
Security is a central piece of this transformation. Giving machines too much agency is a legitimate concern and risk. Healthcare data is not only sensitive—it’s protected by federal and state laws. But compared to current healthcare systems that often rely on aging computer systems vulnerable to data breaches, generative AI offers increased capacity to detect and identify bad actors and to incorporate extra layers of security. AI systems can employ advanced encryption, real-time monitoring, and anomaly detection to protect patient data more effectively than before.
People will be a central part of building and maintaining these systems. Clinicians will still need administrators to make sure systems work smoothly and optimally. Human oversight will be crucial to managing complex situations and escalations and ensuring the technology functions correctly. Ongoing training and support for healthcare professionals will be essential to integrating AI seamlessly into the healthcare workflow.
Just as medical breakthroughs like vaccines, new therapies, and surgical techniques have pushed healthcare to evolve, so too will this advance in administration. Eventually, clinicians will have their own AI agents that can confer with patient agents. This is the key to a more efficient, responsive, and patient-centered healthcare system, where the focus is squarely on delivering high-quality care rather than navigating administrative hurdles.
The journey toward integrating AI into healthcare administration is not just about cutting costs or speeding up processes—it’s about fundamentally transforming how we deliver and receive healthcare. By embracing these technological advancements, we can create a system that is more equitable, efficient, and effective for everyone.
Human Health and the Sustainable Development Goals
Our Human Health investments touch 11 out of the 17 Sustainable Development Goals. The vast majority of our companies in this area are working to ensure healthy lives and promote well-being for all. Companies like Positive Development and Devoted Health are making strides toward reducing inequalities within countries, while Beyond Meat, Welly, and others are ensuring sustainable consumption and production patterns.
Inceptive
Discovering Life’s Languages With Generative Science
In 2021, Jakob Uszkoreit and Rhiju Das founded Inceptive to, in their words, “use deep learning and high-throughput experiments to understand life’s languages,” starting with RNA.
Uszkoreit was one of the eight machine learning researchers at Google who co-authored the seminal paper in 2017 that laid the foundations for generative AI. The first use of this technology was to generate text, images, and video.
Uszkoreit realized that by applying new, similar AI models to science, this groundbreaking technology could help solve some of the biggest questions in medicine.
RNA is a molecule that intermediates how our genetic code (DNA) gets actualized to proteins, which in turn carry out important cellular functions. Messenger RNA (mRNA) first came into broad focus in 2020 as it was leveraged to develop vaccines for COVID-19 in record time. But the Covid vaccines were merely the beginning of RNA’s potential for almost any therapeutic application, from fighting respiratory illnesses to, conceivably, eliminating cancer.
The AI models that Uszkoreit was instrumental in developing are a powerful tool to explore the extreme complexity of biology. Even a relatively simple protein like the spike protein in the Covid vaccine can be coded by over 2.4 × 10 632 theoretically possible mRNA sequences in the known universe. While this immense search space is impossible for humans to fully explore, Inceptive believes that advanced AI models can detect relationships hidden from humans to find mRNA sequences that lead to better drug properties.
Powered by a team with a diverse combination of dry and wet lab expertise, Inceptive has begun partnering with major pharmaceutical companies that will test, validate, manufacture, and eventually distribute the molecules designed in their labs. It takes a village to get the next generation of life-saving drugs to those who need them, and Inceptive is working to create the village that it will take.
A spike protein can be coded by over 2.4 ×
10632 theoretically possible mRNA
sequences.
GenHealth
Predicting Better Healthcare
It’s no secret that the U.S. healthcare system is broken. Americans spend $4 trillion on healthcare annually, but the U.S. has some of the worst health outcomes in the Western world. Better data and analytics can overcome some of these challenges.
GenHealth is pioneering a new approach in healthcare with its transformer-based large medical model. Trained on a vast dataset of 140 million patient healthcare claims and financial data, this model offers insurers, providers, and pharmaceutical companies realistic projections of their patients’ future health based on their past. This collaborative approach, where humans and AI work as co-pilots, allows for real-time feedback that the AI can learn and improve from.
In the near future, the team at GenHealth believes, most major health decisions will be supported by AI—and GenHealth intends to be that AI.
personalized actuarial analysis.
GenHealth’s vision extends beyond the AI model—they are reimagining healthcare by building applications natively on their AI. Leveraging their large medical model, they have built applications that cut 90% of the administrative burden of prior authorizations and a healthcare analytics chatbot that can answer any population health questions of the past, present, and future.
Americans spend $4 trillion on healthcare annually.
$1 trillion comes from administration costs.
Pi Health
cases in 2022. Approximately 1 in 9 men and 1 in 12 women die from the disease.
1 in 9 men and
1 in 12 women
due to enrollment issues. Geography plays a critical role—clinical trials are often limited to large academic centers in cities and not available in community health settings. So does awareness—a lack of patient education around trials and technology gaps in identifying and enrolling patients also contribute to the problem.
Only 2 % to 8 % of eligible cancer patients participate in clinical trials.
Pi Health is using AI to simplify and modernize an archaic trial process that currently involves binders full of paper, spreadsheets, and manual data entry. The startup uses AI to automate tasks, including matching patients with trials, creating clinical documentation, and monitoring during studies. Pi Health also recruits cancer patients from a diverse genetic pool from across four countries: the U.S., India, Australia, and Brazil.
This new software platform will reduce friction and costs while rapidly increasing patient enrollment in trials around the globe, automating manual processes so that data collection can be done faster and at a higher quality, advancing medicine and improving patient outcomes.
Virta Health
A Nutrition-First Alternative to Ozempic
This past year, the use of weight loss drugs like Ozempic skyrocketed across the country. About 1 in 8 adults in the U.S. have used one of these GLP-1 drugs, and about 6% of the U.S. population is currently on one. These drugs are costly, however, and have the potential for short- and long-term side effects.
Meanwhile, Virta Health, a leader in transforming health through personal nutrition and coaching, has emerged as a top alternative amid the Ozempic boom. Virta delivers weight loss results on par with GLP-1s, without drugs or their side effects, at a fraction of the cost. Virta members lose on average 13% of their body weight in one year (most behavioral programs deliver less than 5% weight loss). Virta’s personalized nutrition plans factor in each member’s lifestyle and dietary preferences and provide them with the tools, knowledge, and support they need to make sustainable lifestyle changes to improve their health for the long-term.
Over the past year, enrollment in Virta’s sustainable weight loss solution surpassed enrollments in Virta’s flagship Type 2 diabetes reversal program. In 2023, a staggering 100% of Virta’s new large employer groups contracted with the company for its sustainable weight loss and Type 2 diabetes reversal programs, up from 10% a few years ago. Virta has also proven their approach sustains weight loss results post GLP-1 use.
The company, named to Time magazine’s list of the 100 most influential companies of 2023, also released a new study last year demonstrating Virta’s impact on health equity. The research highlighted significant health improvement and medication reduction for members living across the most and least disadvantaged neighborhoods in the U.S. At one year, all members had seen similar health improvements—including blood sugar control with fewer medications—regardless of where they live.
1 in 8 U.S. adults have used a GLP-1 drug.
Virta members lose 13% of their weight in one year, on average.
Synteny
Synteny’s initial models reached 87 % and 94% accuracy for the detection of Stage 1 and 2 cancers.
Decoding the Immuniverse
The human immune system is a set of cells that has evolved over millions of years to defend us against threats. It has two branches: innate immunity, which is considered our first line of defense, where cells respond to general patterns. With adaptive immunity, our second line of defense, adaptive cells respond to specific threats. T-cells are key cells of adaptive immune response.
T-cells also happen to be where Synteny is focused on making major breakthroughs. Synteny is building the AI platform to solve the recognition code of T-cells for antigens—the molecules from viruses, bacteria, or mutated cancer cells that trigger an immune response. Decoding immune signals to interpret disease biology has been seen as the holy grail for therapeutics and diagnostics developers. Given the sheer complexity of the immune system— 10 quadrillion possible T-cell receptor (TCR) variants, each of which can recognize one or more antigens, for instance—this was until recently a technologically unsolvable problem.
However, by designing novel AI algorithms and wet-lab assays that allow Synteny to generate data orders of magnitude greater in scale than previously possible, they are learning the rules of immune activation and are on a path to solving this biological grand challenge.
Based on insights generated by their platform, Synteny enables partners to develop products in three categories: therapeutics, like cancer vaccines and TCR therapy design; disease detection; and immunotherapy efficacy prediction. These three separate markets are projected to be worth $32 billion in annual sales by 2030.
“By decoding the Immuniverse—as we call it—we can rapidly and scalably design precision therapies which leverage the natural properties of our immune cells to target diseased cells,” says Synteny’s co-founder and CEO, Lilly Wollman.
The company’s early data is extremely promising. Synteny’s initial models reached 87% and 94% accuracy for the detection of Stage 1 and 2 cancers, respectively. Furthermore, the company’s patient stratification models for immuno-oncology (IO) trials achieved 88% accuracy in predicting whether urothelial cancer patients will respond to a certain IO therapy.
We are reimagining financial services, labor marketplaces, and insurance to empower individuals and businesses. We back inclusive finance that leverages technology to improve banking, lending, and insurance. As companies embrace novel work arrangements, we support tools that empower workers and enable collaboration.
A Future Shaped by AI Innovation
By James Joaquin
As we look to the future, we believe the economic landscape will be reshaped by AI-fueled innovation. Advances in data analytics, enterprise tools, and business software will redefine economic health, offering substantial benefits to individuals and businesses alike.
We believe the biggest advances will come in several key areas. Small-to-medium-size business (SMB) tools and core fintech will boost how businesses operate and interact with consumers. Labor marketplaces will redefine valuable job skills and more closely align employers with workers. And industries like insurance that have long struggled with boom-and-bust cycles and customer dissatisfaction will find smoother paths to operational stability and customer retention. In each case, fraud will remain a potent risk, and AI tools will also improve at detecting and eliminating bad actors.
Here’s a
snapshot of the future we predict:
01 AI fraud will require AI anti-fraud.
Bad actors will utilize generative AI, which mimics natural human behavior, to successfully execute financial fraud with greater frequency and cost to the system. In response, a new wave of cybertech startups utilizing custom AI models will shield businesses and consumers from attacks.
03
Record numbers of businesses will transfer to their employees.
Two factors will accelerate business transfers: The “silver tsunami” of retiring baby boomers will drive the turnover of nearly 8 million privately owned businesses. And reduced venture funding between 2020 and 2022 will prompt more founders to sell. The economy will need better mechanisms for connecting sellers with values-aligned buyers and new tools to scale business transfers.
04
Labor marketplaces will shift to high-value, full-time positions.
In the past decade, we saw the creation of massive labor networks like Uber delivering flexible staffing of commodity low-value human labor. As AI takes over many dull, dirty, and dangerous jobs, we will see the human labor marketplaces of the future focused on specialized high-value, full-time positions. AI-driven credentialing and matching will also turbocharge labor marketplaces and professional recruiting to align companies’ specific needs with candidates’ specific skills.
02 Individuals and SMBs will get easier access to credit.
Consumers and small businesses will benefit from new underwriting models that incorporate alternative data (such as personal and business cash flow) that augment traditional methods of determining creditworthiness. We believe the Consumer Financial Protection Bureau’s Q4 Notice of Proposed Rulemaking will make lenders even more comfortable using new data metrics in underwriting decisions.
05 Property and casualty insurance will offer more coverage at lower rates.
The next wave of property and casualty insurance underwriting and distribution will use AI to underwrite with better and more accurate data and to streamline existing workflows such as communication between brokers and carriers. While incumbent property and casualty insurers will be forced to raise costs to cover past losses, disruptors will be able to leverage more efficient workflows to offer individuals and businesses substantially lower rates.
The Bold Promise of AI for Financial Well-th
By Katie Giometti
The transformative power of artificial intelligence in financial services is not just promising—it’s imminent. At Obvious, we see the confluence of digital interconnectivity and generative AI as a game changer for money management, particularly for everyday Americans.
Historically, top-tier wealth management has worked on the assetsunder-management (AUM) model. The high cost of expert human advisers has made high-quality financial service a privilege only for people with substantial assets. A 2023 Northwestern Mutual study found that only 37% of Americans work with a financial adviser, compared to 70% of wealthy Americans. Those with more meager wealth, or no wealth, have limited to no access to comprehensive financial advice.
This inefficiency is expensive. In the absence of affordable options, younger generations are turning to unreliable financial sources. A recent survey found that almost 1 in every 2 members of Gen Z relies on TikTok for financial advice. More than half of them are overexposed to high-risk asset classes like crypto and meme stocks, and 19% admitted they hold only crypto, leaving them vulnerable to extreme volatility and financial instability. Meanwhile, older generations without access to high-quality financial advice are often exposed to too much market risk as they age, fall prey to high-interest debt, and aren’t maximizing Social Security benefits.
For the majority of Americans, the term “wealth management” is irrelevant because they lack wealth; they need to reach the first rung of financial wellness first. And we believe AI is poised to finally make financial wellness a reality for more Americans in a reliable, fast, deeply personal, and affordable way.
One major AI advance is the ability to understand siloed financial accounts in a detailed and cohesive picture. Combining accounts is not new, but understanding them is. AI presents the opportunity to make sense of messy, unstandardized transaction data and make better, quicker recommendations.
AI models can also incorporate unprecedented personalization and insight. This integration foreshadows models that can offer tailored financial advice based on an individual’s specific history, situation, and goals. The picture can change quickly with new information, such as losing a job, making a major purchase, or receiving a financial windfall.
A decade ago, we thought that this was the promise of roboadvisers. And while roboadvisers have succeeded in increasing access to wealth management, there is sizable room for improvement. Roboadvisers have scant personalization capabilities and limited investment options, and they can’t design financial plans sufficient for the complexity of an individual’s life. A high-end wealth manager can still offer more personalized financial planning, employ more sophisticated investment strategies, and produce higher returns than a roboadviser. However, by the end of the decade, AI-based advisers will prove faster, cheaper, and more comprehensive than existing advisers relying on traditional tools. Even primitive AI models can track global market trends, read the Wall Street Journal, and process all CNBC commentary before a human adviser even wakes up.
We’re already seeing brokerages and banks broadly incorporating many of these tools and abilities. Morgan Stanley recently announced a plan to provide an AI co-pilot to wealth advisers to sit in meetings, rebalance portfolios, and generate reports. Newer companies are taking an AI-first approach with one-stop
shops for investing, budgeting, tax, and estate planning. However, many of these solutions are employing AI firepower for the benefit of wealth management. We’re excited to see newer solutions come to market focused not on wealth management but on financial wellness, and we’re encouraged by the work that our portfolio company Brightside (page 58) is doing in this space. For example, with U.S. credit card debt at a record $1.13 trillion, we see a large opportunity to help everyday Americans automatically consolidate and manage debt according to their personal circumstances.
Financial wellness is far from the easiest category in which to deploy AI. Financial advisers are held to a high fiduciary standard to serve their clients’ best interests. AI will need to adhere to these standards, along with the September 2024 tightened regulations that apply to more types of accounts, including retirement accounts. Additionally, the fiduciary duty will require banks and brokerages to protect consumers and their assets from the risks of automated systems.
The benefits, however, far outweigh the risks. Nearly 75% of Americans experience financial stress that influences their mental and physical health and personal relationships. Almost 40% of Americans lack the savings to cover even a $400 expense. And too many young people are struggling to eliminate debt and build a reliable nest egg.
We see AI-powered financial wellness as a powerful tool to neutralize and even reverse these trends. When deployed strategically, equitably, and with appropriate oversight, these tools will bring dramatic opportunities to millions, and possibly billions. Through our partnerships with founders and visionaries, we are excited to be helping shape a better and more secure financial future for everyone.
Economic Health and the Sustainable Development Goals
The Economic Health companies we invest in are making progress toward eight Sustainable Development Goals. The two goals the majority of our companies in this area touch are Decent Work and Economic Growth— which involves inclusive and sustainable growth and full and productive work for all—and Industry, Innovation, and Infrastructure, which includes building resilient infrastructure, promoting sustainable industrialization, and fostering innovation. Other goals include Quality Education, Life Below Water, and Reduced Inequalities.
Brightside The ER for Financial Health
Bethany fell behind on rent and was facing eviction. Jessica needed help managing more than $45,000 in credit card and student loan debt. Amy’s mom needed heart surgery and didn’t have enough saved to cover the deposit for the procedure.
60,000 families served
$41M saved
What these women had in common—besides facing financial challenges—was that their companies offered Brightside as a benefit. Brightside provides personalized financial support and solutions for employees, especially the working families who make up a large part of our labor force and are often under financial pressure. To date, Brightside has served 60,000 families with 160,000 unique financial needs, putting roughly $41 million back into their pockets (a week’s pay per person, on average).
Some 71% of Americans say that money is their biggest source of stress. Financially stressed employees miss 16 more days of work per year, on average, and they are two times more likely to look for a new job.
Brightside offers solutions to stressful money challenges through their comprehensive model, Financial Care. This model involves on-demand access to financial experts with real solutions to help employees navigate life.
Tom Spann co-founded the company in 2017, after a long career in healthcare, when he realized how much a person’s financial health affects every aspect of their lives.
“Financially sick people very often need urgent care. You’ve got to stop the bleeding. Then, they need primary care,” says Spann. “They don’t need financial wellness, which is focused on financial planning for folks who have money to invest.”
In the case of Bethany, who was facing eviction, her Brightside Financial Assistant connected her with a grant that covered her back rent and helped her with a budget to get her finances back on track. Jessica’s Financial Assistant helped her consolidate her debt into a single, lower interest rate and apply for student loan forgiveness. Amy, who was trying to help her mother schedule surgery, was worried she’d have to use high-interest payday loans to make ends meet. Her Financial Assistant helped her secure the $5,000 she needed and helped her come up with a plan to rebuild her savings.
Incredible Health
Over 1 Million Served
Last March, Incredible Health reached an incredible milestone. The company is now the largest healthcare career marketplace in the U.S., trusted by over 1 million nurses and 1,500 hospital locations nationwide.
79% of nurses intend to stay in the field until retirement.
88% of nurses believe that staffing shortages are having a detrimental impact on patient care.
Iman Abuzeid and Rome Portlock co-founded Incredible Health to help healthcare professionals find and do their best work. The company enables hospitals to apply to nurses instead of the other way around.
Among the 1,500 hospitals currently working with Incredible Health are Johns Hopkins Health System, Stanford Health Care, Kaiser Permanente, and Cedars-Sinai Medical Center.
To shine a light on critical challenges nurses face today, the company releases an annual “State of US Nursing” report, filled with insights based on the data of the more than 1 million nurses on the platform and a survey of more than 3,300 registered nurses.
The 2024 report identified consistent issues in the nursing field, along with areas for improvement. Among the encouraging findings were that 79% of nurses intend to stay in the field until retirement.
However, three significant challenges continue to affect the field: the nursing shortage, concerns about workplace safety, and financial instability.
An alarming 88% of nurses surveyed believe that staffing shortages are having a detrimental impact on patient care, with 63% reporting that they were assigned to care for too many patients at a time.
Burnout and trauma from the COVID-19 crisis had an alarming number of nurses reporting poor mental health, but the 2024 report suggests a slow but steady improvement of 6% over the past year.
Concern about nurse safety on the job was a major issue in this year’s report. Some 50% of nurses reported having been verbally and/or physically assaulted by a patient or a member of a patient’s family within the past year. By shining a spotlight on issues requiring immediate attention from hospital management, Intelligent Health is helping hospitals better support nurses.
Prism Making Credit Scores More
Inclusive
Access to credit is a major problem in the U.S. Over 100 million Americans have a low credit score or no credit score at all, yet only a tiny fraction will ever actually default on a loan.
100M+ Americans have a low credit score or no credit score at all.
$2B+ in credit extended using Prism’s technology
Major aspects of a typical consumer’s financial life—like rent payments, income sources, savings, and investments—fail to be incorporated into mainstream credit assessments. Without a way to accurately assess whether a potential customer is creditworthy, financial institutions are often hesitant to extend them credit.
Prism Data, a risk analytics company, was created to help solve this problem by harnessing the power of “open banking” to make credit scores more accurate and inclusive. Prism enables automated analysis of line-by-line financial transaction data as part of credit assessments, which have traditionally relied on credit reports alone. Open banking regulations and technical infrastructure make this possible by allowing consumers the ability to access and share their financial transaction data in real time.
Prism’s open banking infrastructure and analytics platform give financial providers a more comprehensive and accurate understanding of a consumer’s financial life, delivering insights that lenders can use to improve underwriting capabilities, minimize first-party fraud, and better manage their portfolios. To date, Prism’s technology has been used to extend over $2 billion in credit.
Prism does all this through CashScore, its automated, machine learning-enabled scoring of a consumer’s financial transactions. CashScore measures core financial information—like income, savings, and expenses—that’s excluded from mainstream credit reports. CashScore performs roughly as well as the FICO Score or VantageScore in predicting credit default risk, even if a consumer has no credit report. When traditional credit data is available, Prism’s CashScore provides significant orthogonal value to improve underwriting accuracy.
Since the launch of CashScore in 2022, Prism has seen significant traction, signing more than 20 clients and partners and completing over two dozen successful pilots, including with some of the country’s largest banks.
Dexterity
A New Frontier for Robots
The rise of e-commerce has brought us many things, including almost anything we want delivered almost instantly to our doorsteps. Less known is that it has also brought us a new frontier for robot development.
Dexterity is at the forefront of this frontier, using AI, machine learning, and platform-based robotic intelligence to make warehouses more productive, safe, and efficient.
Last fall, Dexterity announced a partnership with FedEx to automate one of the trickiest tasks its employees face: loading a truck with packages. Their new robot, the DexR, uses AI to stack rows of boxes inside a delivery truck as efficiently as possible.
FedEx handles some 15 million packages a day. Truck loading has long been considered one of the most challenging tasks in warehouse hubs. Manual loading is taxing on workers, and previous technology approaches have not been able to handle the complex decision-making required to stack a variety of boxes.
Dexterity focuses on the complexity of truck loading by giving robots a suite of intelligences including the ability to see, touch, reason, and move quickly to pack trailers. With every new box presented to the DexR, Dexterity’s AI
Dexterity’s AI software takes
software takes 500 milliseconds or less to assess billions of wall build possibilities.
The robot’s unique dual-arm design and onboard AI enable it to match operational loading speeds and packing requirements without knowing the size, weight, or shape of boxes before they arrive at the robot—a process described as “playing 3D Tetris.”
Each time it places a box in a stack, the system uses force feedback to ensure the package fits tightly, and it also scans the stack using cameras and depth sensors to see how it compares to its existing model. Any discrepancy requires the robot to adapt its stacking plan as it goes along.
A few months after the FedEx partnership was announced, Sagawa, one of Japan’s largest logistics companies, initiated a similar partnership with Dexterity to mitigate a labor shortage by using the DexR to tackle the most physically demanding tasks facing their team.
500 milliseconds
or less to assess billions of wall build possibilities.
Obvious Impact: Full Portfolio
From industrial innovation to climate action, we are excited to share the measurable positive impact happening across all the companies we have invested in. In the table that follows, you can explore each SDG and dive into a detailed accounting of the number of Obvious companies moving the needle on that goal.
It’s no surprise that the goals most frequently impacted map nicely to our three pillars of Planetary Health, Human Health, and Economic Health. Each year we will continue to update this reporting as an impact lens across the entire Obvious portfolio.
Planetary Health
Human Health
Economic Health
Obvious became one of the first venture capital firms in the world to become a Certified B Corporation in 2017. B Corps are businesses that meet the highest standards of verified social and environmental performance, public transparency, and legal accountability to balance profit and purpose.
Our impact score increased from 83 to 108 in 2023, after a two-year recertification process. We perform biannual audits to ensure we’re putting our values into practice with our employees, our corporate governance, our partners, our communities, and our environment.
Writers and Editors: Emily Brady, Daniel Stone
Contributors:
James Joaquin, Vishal Vasishth, Andrew Beebe, Kahini Shah, Rohan Ganesh, Katie Giometti, Anku Madan
Copy Editor: Victoria Gannon
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Obvious World Positive Report 2025 by Obvious Management Services LLC is licensed under CC BY-ND 4.0. To view a copy of this license, visit https://creativecommons.org/licenses/by-nd/4.0
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