CXO TechBOT July 2025

CXOTechBOT

Your Digital Sherpa to discover Tech Enigma

Embark on a thrilling expedition into the future of digital advancement with CXO TechBOT, your ultimate gateway to unlock the boundless potential of technology.

JOIN THE COMMUNITY

MAGAZINE | NEWSLETTER | WEBSITE

The CXO TechBOT Team

CEO & Editor-In-Chief

Swati Gupta

Chief Vision Officer

Puneet Agarwal

Managing Editor

SuhasVittal

Content Editors

Suhas Vittal

Hanifa Khatoon

Zainab Sayyed

Prachi Gupta

Design Head

Vanshika Gupta

Head of Digital Strategy, Delivery & Operations

Priyanka Gautam

Communication Manager

Bhumika Nandhani

Digital Partner

Fusionflare Media

Video & Production Manager

Kush Bhalla

Sales & Development Head

Disha Gautam

Event Coordination

Disha Gautam

Hanifa Khatoon

Mayuree Rastogi

Creative Manager Development Team

Hradyesh Chaturvedi

Alok Bhade

Naman Hooda

Customer Success Manager

Zainab Sayyed

Sonal Mishra

MESSAGE THE EDITOR from

We are living in a transformative era, one where deep technologies like quantum computing, synthetic biology, AI, advanced materials, and space technologies are no longer confined to research labs. They are entering boardrooms, policy frameworks, and even our daily lives This is not just a technological shift; it is a paradigm shift in how we solve global challenges, from climate resilience to cognitive health, from energy transitions to national security.

As Editor-in-Chief, I see this magazine as a bridge between visionaries and policymakers, scientists and entrepreneurs, academia and industry Our mission is to spotlight the trailblazers, dissect the breakthroughs, and provoke the big questions: How do we scale ethical innovation? What does sovereignty mean in a world of AI and quantum control? Where will the next DeepTech unicorns come from?

In this issue, we explore the defining forces of the DeepTech Decade, feature thought leadership from global experts, and delve into India’s potential to emerge as a DeepTech powerhouse

The journey ahead is complex, but filled with immense possibility It demands courage, curiosity, and collaboration across disciplines and borders. We invite you to join us not just as readers, but as participants in shaping the future of deep innovation

The next decade won’t be led by those who follow trends, but by those who build what doesn’t yet exist.

Warm Regards

Swati Gupta CEO & Editor-in-Chief

Blank with Palash

Ecosystem-Led Growth: How Strategic Alliances Are Driving AI and Cloud Adoption

Rewiring Innovation: A Deep Dive with Subhajit Sarkar on Gen AI, DeepTech, and Human-Centric Transformation

Digital Sovereignty and DeepTech: Redefining Global Governance and Tech Policy

In an era marked by rapid digital transformation, the concepts of (DeepTech) evolution of global governance and technology policy. As nations, corporations, and citizens become increasingly reliant on digital infrastructure, questions of autonomy, security, control, and innovation are reshaping the global power dynamics. This article explores how digital sovereignty and DeepTech intersect, and why they are pivotal in reimagining tech policy in a fragmented yet hyperconnected world.

Understanding Digital Sovereignty

Digital sovereignty refers to a nation’s ability to control and regulate its digital infrastructure, data flows, and technological ecosystem in a manner that aligns with its political, economic, and societal values. It is a direct response to the growing dependence on foreign technologies—particularly from the United States and China—and the risks associated with surveillance, monopolies, and geopolitical dependencies.

Countries like France and Germany have been vocal proponents of digital sovereignty, advocating for European alternatives to American cloud providers,

efforts are often hampered by geopolitical rivalry and conflicting interests. Digital sovereignty introduces a double-edged sword in this context—it enables nations to safeguard national interests but risks fragmenting the global internet into “splinternets,” where access and regulations differ widely across regions.

Tech Policy Dilemmas: Innovation vs Regulation

One of the biggest challenges in formulating global tech policy is balancing innovation and regulation. While data localization and content moderation laws help protect sovereignty, they can also restrict innovation, increase operational costs, and stifle cross-border collaboration.

DeepTech exacerbates this tension. AI algorithms, for instance, thrive on vast, diverse datasets. Stricter data boundaries might hinder the training of these models. Similarly, quantum computing requires international scientific partnerships that may clash with national security priorities.

Forward-thinking tech policy must find a way to harmonize data protection, intellectual property rights, and ethical AI standards without compromising scientific progress. This requires dynamic, multi-level governance models where nation-states, corporations, and international institutions collaborate on shared standards while preserving local control.

Digital Sovereignty and Tech Nationalism

and TikTok, and Russia’s attempt to build a sovereign internet. These developments reflect how digital tools have become instruments of national power and diplomacy.

However, excessive tech nationalism could backfire by isolating countries from global supply chains, talent pools, and investment ecosystems. A balanced approach—what some experts call “open strategic autonomy”—is essential to maintain global competitiveness while protecting national interests.

Digital sovereignty is also fueling a new wave of tech nationalism—where countries aggressively pursue homegrown technologies and impose restrictions on foreign firms. While this fosters domestic innovation and strategic resilience, it also risks leading to protectionism, digital trade wars, and reduced global interoperability.

Recent examples include India's ban on Chinese apps post-Galwan conflict, the U.S. restrictions on Huawei

AI ethics frameworks to ensure responsible use of intelligent systems globally.

Climate-focused DeepTech (like clean energy tech, smart grids, carbon capture) where shared human interest transcends national rivalries.

Joint R&D projects on quantum computing, space tech, and genomics that require pooled expertise and funding.

International alliances like the Quad (India, US, Japan, Australia) and EU-U.S. Trade and Technology Council are examples of how like-minded democracies can shape global tech norms collaboratively.

The Road Ahead: Policy Recommendations

Invest in Strategic DeepTech: Countries should establish sovereign DeepTech funds, innovation clusters, and public-private partnerships to reduce reliance on foreign technologies.

Build Digital Infrastructure Autonomy: Develop national cloud platforms, 5G networks, and chip manufacturing facilities to assert infrastructure

Create Ethical and Interoperable Standards: Work with international bodies to co-develop policies that ensure interoperability and uphold human rights.

Educate for Digital Citizenship: Build societal awareness around digital rights, privacy, and data governance through civic engagement and education.

Wrapping up

Digital sovereignty and DeepTech are no longer abstract policy debates; they are at the heart of national competitiveness, security, and identity. In the coming decade, nations that can navigate the complex interplay between control and openness, sovereignty and collaboration, innovation and regulation will define the new global digital order. The future of tech policy lies in cooperative resilience where nations lead with purpose, partner with trust, and innovate with shared values.

REIMAGINING INDIA: FROM CONSUMER TO CREATOR, FROM MOMENTUM TO MASTERY, FROM SCALE TO SOVEREIGNTY!

India now stands tall as the world’s fourth-largest economy, with a nominal GDP crossing $4 trillion and a robust 8.2% real GDP growth in FY2024—among the fastest globally. This remarkable transformation is fueled by multiple high-impact engines:

•The IT-BPM sector contributed $253.9 billion in FY2023, employing 5.4 million professionals.

•Renewables surged with 24.5 GW of solar and 3.4 GW of wind added in 2024; total capacity now at 217.62 GW, on track for 500 GW by 2030.

•Digital Public Infrastructure—anchored by UPI and Aadhaar—processed over 130 billion transactions in 2024.

•Internet user base is set to cross 900 million by 2025. The 3rd-largest startup ecosystem, home to 119 unicorns valued at over $354 billion (as of Jan 2025).

•Hosting 55% of the world’s Global Capability Centers (GCCs), powered by a vast STEM talent pool.

•Backed by a large domestic market, digitally native population, and forward-leaning policies

This is nothing short of phenomenal progress—a bright beacon lighting the path forward.

let’s not assume tomorrow’s strategy on yesterday’s momentum.

We must ask the defining questions: What could throw a wrench in the works? What risks lie ahead? Which forces will truly shape India’s destiny?

Looking Through the PRISM: The Global Lens

Two recent global economic developments bring some questions into sharper focus:

•On April 2, the U.S. announced a new round of tariffs, shaking global markets. Indian stock market analysts, however, remained calm—and rightly so. Their confidence stemmed from a specific macroeconomic buffer: India's relatively low trade surplus with the U.S. (~USD 36 billion). Experts suggested this could be offset through couple of strategic imports like defense or oil

•India overtook Japan to become the world’s fourth-largest economy—a milestone of national pride and a marker of rising global stature.

While, As an Indian, I take pride in our economic resilience and rising global position, but when viewed through our Peerless Prism, a deeper question emerges: Our resilience to global phenomena seems to stem less from robust fundamentals and more from our limited exposure and relatively modest contribution to global trade. Are we mistaking insulation for invincibility?

What’s truly driving our phenomenal economic growth?

The Trade-to-GDP Ratio: A Double-Edged Sword

India’s trade-to-GDP ratio sits at 45%. Excluding software/IT exports, and defense and oil imports, it drops to just 36%.

The advantages are clear:

•Shields India from global shocks and supply chain disruptions.

•Domestic demand remains a stable engine of growth.

• Allows for policy flexibility and currency stability.

But there are risks as well:

• Reflects limited global competitiveness.

•Indicates weak innovation spillovers.

•Highlights underutilized export potential.

Can a nation dreaming of economic leadership afford to be so lightly stitched into global value chains? This gap is more than a missing puzzle piece—it’s a roadblock to deeper global integration and lasting value creation.

The Hidden Fragility: Structural Economic Challenges

India’s ascent is real—but it remains incomplete. Several structural indicators expose the fragility beneath the momentum:

•Private Final Consumption Expenditure (PFCE) exceeds 55% of GDP, showing a heavy reliance on domestic consumption.

•Over 80% of the workforce remains trapped in informal, low-productivity employment.

•Manufacturing stagnates at 17% of GDP, despite years of Make in India efforts.

•R&D investment is under 0.7% of GDP—too low to power innovation and deep tech adoption.

•Regional disparities persist, with Southern and Western states far ahead of others.

Our current growth model emphasizes volume over value, scale over sophistication, and population over productivity. To move beyond momentum and build lasting economic leadership, we must evolve—from being a passive participant to an active creator in global value chains. This shift requires more than incremental reform. It demands a foundational transformation—one that only DeepTech can deliver.

Why DeepTech is India’s Strategic Imperative

DeepTech is more than a sector—it is a strategic enabler that fuses science, technology, and innovation to secure India’s future across three vital dimensions:

1. Strategic Sovereignty: Owning the Future, Not Renting It In a world defined by contested borders, cyber threats, and technological one-upmanship, strategic sovereignty is no longer optional—it’s existential. DeepTech forms the frontline of national independence by reducing reliance on foreign technologies and enabling homegrown breakthroughs.

While Chandrayaan-3—powered by indigenous cryogenics and autonomous navigation—earned global acclaim, equally vital but less visible innovations are shaping India’s sovereign capabilities:

• QNu Labs is pioneering quantum-safe cryptographic systems, securing India’s digital infrastructure against future quantum-era threats.

•Sagar Defence is developing autonomous unmanned surface vessels, enhancing maritime surveillance and national security.

Though limited in number, these efforts hint at the transformative role deep tech can play in areas where strategic advantage, security, and long-term self-reliance matter most.

“He who holds the code holds the command.” - In new world order, owning the core technology—from source code to silicon—is the ultimate lever of strategic power.

2. Economic Muscle: From Bench Strength to Global Brilliance

India excels in IT services and talent—but global respect and pricing power demand innovation, not just scale.

Despite exporting goods worth around $450 billion, much of India’s export basket remains concentrated in low- to mid-value segments—textiles, petroleum products, and basic chemicals. In stark contrast, nations like Israel, Switzerland, and South Korea have carved global niches in high-value, Deep Tech-led exports.

PALASH GUPTA

Product R&D & Engineering Strategy Leader

Verint

Palash Gupta is a Product Engineering and Strategy leader known for establishing, scaling and playing leadership Global Capability Centres for tech companies and DeepTech startups in India. A thought leader in technology space, He has served Nasscom National Product Council, led DeepTech Club, mentoring at IITs and IIMs and extensively contributed to the country's policy making technology & business ecosystem.

https://www.linkedin.com/in/palashgupta/

•Israel (~9M people) exported $160B in 2023, driven by semiconductors and cybersecurity

•Switzerland (~9M) exported $440B, led by biotech and precision engineering

•South Korea (~52M) exported $680B, backed by 4.8% of GDP invested in R&D and a robust advanced manufacturing base

Per capita income illustrates the real disparity:

•Switzerland ~$94K

•Israel ~$55K

•South Korea ~$35K

•India ~$2.7K

This gap exposes the hard truth: Innovation depth beats population size every time.

Consider Sankhya Labs, developing India’s own chip IP for 5G, radar, and aerospace—technologies that are not only economically valuable but foundational to strategic autonomy. Or Planys Technologies, which is pushing the frontiers of maritime defense through advanced underwater robotics, offering indigenous solutions for inspection and surveillance in critical infrastructure. India’s future isn’t in volume—it’s in sophistication. DeepTech must power the leap from talent factory to global innovation leader.

“Economic power today is less about size, and more about the strategic depth of innovation.” India’s economic future must shift from scale to sophistication, powered by DeepTech

3.Societal Scale Impact: Building for Billion

India’s most critical challenges—clean water, healthcare, energy—can’t be solved through incremental change. They demand bold, scalable, tech-enabled solutions, customized to a 1.4-billion-strong population. Yes, Bharat Biotech’s Covaxin showed India can create and distribute health solutions at scale. But quieter revolutions are underway:

•Uravu Labs has built renewable-powered atmospheric water generators that extract drinking water from air—without electricity.

•Niramayi Health Analytix is using AI for early cancer detection, enabling affordable diagnostics at the grassroots level

These ventures exemplify a deeper capability: solving first-mile problems with frontier science.

“In India, scale is not a choice—it’s a constraint.”DeepTech turns this constraint into a competitive advantage, enabling India to build resilience—not just respond to crises.

DeepTech: India's Blueprint for a New Era

Our early triumphs in space, quantum, biotech, and semiconductors prove DeepTech springs from necessity, not novelty. Now, we must scale up massively, redefining growth, closing critical gaps, and future-proofing our economy. This isn't just about survival; it's how India will lead, thrive, and inspire the world.

DeepTech transcends mere technology; it's India's transformation engine. It empowers our people with cutting-edge skills, fuels a high-value job economy, safeguards our environment, and fortifies national security. This is how India converts its demographic dividend into an innovation powerhouse.

National Strategy, Not Just Economics. This extends beyond an economic play—it's India's national strategy. To become a top-three global economy and a genuine world leader, DeepTech must be at our core. It unleashes our scientific talent, embeds India firmly in global value chains, and powers the IP-rich industries of tomorrow.

A Necessity for All - From Ambition to Action. DeepTech is no luxury; it is an absolute necessity. From public health and clean water to agriculture, climate change, and cybersecurity, it addresses India’s most pressing challenges with unprecedented scale and speed. Ultimately, DeepTech embodies the full spectrum of human prosperity—physical health, mental well-being, social equity, economic opportunity, environmental balance, and cultural

vibrancy. By democratizing technology and innovation for all 1.4 billion citizens, we strive to build a society grounded in both equality and equity.

The blueprint is clear the efforts are on, —and the onus now rests on all of us:

•NITI Aayog’s Frontier Tech Cell – AI, blockchain, and Atal Innovation Mission

•Department of Science & Technology (DST) –Quantum Mission, advanced materials, cyber-physical systems

•Department of Biotechnology (via BIRAC) –Biotech and healthcare innovation

•Ministry of Electronics & IT (MeitY) –Semiconductors, supercomputing, AI, Bhashini

•Ministry of Defence’s iDEX – Défense Deep Tech including drones and autonomous systems

•ISRO & IN-SPACe – Space-tech with private sector participation

• Office of the Principal Scientific Adviser –National science and technology missions

•Ecosystem enablers for nurturing DeepTech –nasscom Deeptech and our premium

The future of India’s DeepTech revolution no longer hinges on vision—it now demands bold execution and relentless speed and scale, driven by a shared national purpose.

Point Black with Palash:

Peerless Prismatic Precision.

We'll dissect with unparalleled clarity the forces shaping India's economy, technology, and future—delivering insights with a peerless attitude and unmatched precision.

*All views are in personal capacity and are not representative of the views of organizations for whom, I work or am associated.

CIO Leadership Symposium & Excellence Awards

Join us for the most prestigious celebration of tech-enabled leadership and sustainable transformation.

At FutureFirst 2026, we spotlight the CIOs redefining the digital frontier driving growth, resilience, and purpose-led innovation across industries.

Why Partner with Us?

Stand alongside the most influential tech decision-makers and amplify your brand with:

Nationwide Media & Digital Visibility

Premium On-Ground Branding & Expo Space

Exclusive CXO Interviews & Thought Leadership Features

Curated 1:1 Networking with India’s Top CIOs

Let’s celebrate the tech visionaries building a sustainable, smarter future. Contact for Sponsorship & Partnerships: Date:19 Feb 2026 | Location: New Delhi th 2 0 2 6

Akums Embraces TECHNOLOGY TO TRANSFORM PHARMACEUTICAL MANUFACTURING

through Innovation

In today’s pharmaceutical industry, technology is more than just a tool - it is a strategic necessity. As regulatory expectations increase, market demands grow more complex, and global competition intensifies, pharmaceutical manufacturing is increasingly turning to technology to drive operational efficiency, scalability, ensure quality, and precision.Akums Drugs & Pharmaceuticals Limited recognizes this critical imperative and has embraced advanced technologies to drive operational excellence, maintain superior quality standards, and promote continuous innovation.

Positioned at the forefront of this industry transformation, Akums has seamlessly integrated technology into its core operations, enabling the company to evolve into a future-ready leader dedicated to shaping the future of pharmaceutical manufacturing.

By leveraging state-of-the-art automation, digitalization, and data-driven decision-making, Akums consistently achieves higher productivity levels while adhering to the most rigorous quality standards. The company’s commitment to innovation is reflected in its continuous investment in research and development, advanced manufacturing technologies, and quality assurance systems. This holistic approach not only ensures the delivery of safe, effective, and high-quality pharmaceutical products but also positions Akums as a resilient and agile organization ready to meet future industry challenges.

Redefining Possibilities in Pharma

The future of pharmaceutical manufacturing lies at the intersection of advanced science, modern technology, and continuous innovation. Akums has integrated advanced technology into every aspect of its operations, redefining possibilities in pharmaceutical manufacturing and development.

In FY 2024-25, Akums achieved a consolidated turnover of INR 4,170 crores, reinforcing its position as a leading player in the industry. The company’s extensive portfolio includes 973 DCGI approvals and over 4,000 commercialized formulations across more than 60 dosage forms. With a strong emphasis on research and development, Akums invested INR 130 crore in FY25over 3% of its revenue - highlighting its commitment to innovation.

Akums’ strength is further supported by 12 world-class manufacturing facilities and 4 state-of-the-art R&D centers staffed by over 400 scientists who focus on developing novel drug delivery systems and improving existing formulations. This technological and scientific prowess enables the company to meet evolving industry demands while delivering innovative solutions that improve healthcare outcomes globally.

As a leading pharmaceutical Contract Development and Manufacturing Organization (CDMO) in India, Akums

Sandeep Jain

Sanjeev Jain

has made significant investments in advanced manufacturing technologies, automation, and data integrity tools. Its success is driven by technology-enabled processes, a skilled workforce, visionary leadership, and collaborative partnerships - all aligned with a shared vision of making healthcare more accessible and transformative.

Through its unwavering dedication to innovation, Akums continues to set new benchmarks in pharmaceutical manufacturing, paving the way for a healthier, more empowered future.

Built on Values, Driven by Technology

Founded in 2004 by brothers Sanjeev Jain and Sandeep Jain, Akums grew from a shared vision to serve the nation through enterprise. Coming from a humble middle-class background, the Jain brothers were inspired by the values instilled by their late father, Shri D.C. Jain, whose dedication and resilience shaped their business philosophy. What began as a small pharmaceutical trading store in Chandni Chowk, Old Delhi in 1984 has evolved into India’s largest Contract Development and Manufacturing Organization (CDMO) - a transformation powered not just by vision, but by early and bold investments in advanced technologies.

As Founders and Managing Directors, Sanjeev and Sandeep Jain have been instrumental in driving Akums strategic growth and transformation. Their leadership goes beyond business development, focusing equally on talent, innovation, operational excellence, and ethical integrity. Sanjeev Jain leads Akums business expansion and global strategy. Through strategic partnerships, international alliances, and market diversification, he has significantly scaled the company’s presence and reinforced its reputation as a reliable, quality-focused pharmaceutical partner.

Sandeep Jain champions a people-centric leadership style that aligns employee empowerment with organizational performance. He emphasizes operational excellence and the consistent delivery of high-quality pharmaceutical products. His leadership has fostered a high-performance culture supported by

streamlined processes, strong quality frameworks, and a workforce that is agile, skilled, and innovation-driven.

Akums is harnessing the power of technology across key functions - including customer relationship management, legal, procurement, planning, and data analysis - to drive productivity, enhance transparency, and enable data-driven decision-making at every level. This digital integration empowers teams and leaders alike to act with greater speed, clarity, and confidence. At the helm of this transformation are brothers Sanjeev Jain and Sandeep Jain, Founders and Managing Directors, whose strategic foresight has consistently placed technology at the core of Akums growth. Their leadership is defined not only by a clear vision but also by a passion for building future-ready teams and embedding innovation into every layer of the organization. The Jain brothers strongly believe that people and technology together drive lasting success. Under their guidance, Akums has cultivated a culture where tech-driven decision-making, agile execution, and continuous improvement are woven into the company’s DNA. Today, Akums stands not just as a pharmaceutical leader, but as a beacon of how technology, purpose, and people can converge to build a healthier, more empowered future.

Focus on R&D and Innovation

At the forefront of pharmaceutical innovation, Akums has positioned research and development as a strategic cornerstone of its growth and value creation. Operating four state-of-the-art R&D centres, the company is backed by a team of over 400 highly quali ed scientists, formulation experts, and technical professionals with deep expertise across a wide range of therapeutic segments. Akums R&D capabilities are focused on developing innovative, high-quality, and cost-e ective formulations that address evolving patient needs and meet global market demands. This commitment to innovation has resulted in the successful launch of numerous rst-in-market products in India, particularly in fast-growing segments such as dermatology, cosmeceuticals, nutraceuticals, and key pharmaceutical categories.

What sets Akums apart is not only its ability to innovate but also its proven excellence in technology transfer. The company has built robust, scalable systems that ensure smooth and efficient transitions from lab-scale development to full-scale commercial productionwithout compromising on quality, regulatory compliance, or timelines. Through an integrated approach that combines R&D, regulatory support, and advanced manufacturing, Akums accelerates time-to-market for its partners. This capability has made the company a trusted strategic partner for both Indian and global pharmaceutical players. Whether developing complex generics, novel drug delivery systems, or tailored formulations, Akums continues to lead with science, translating innovation into meaningful healthcare outcomes for patients worldwide.

Innovating Today for a Healthier Tomorrow

Akums Drugs & Pharmaceuticals stands as a leader in pharmaceutical innovation, with a portfolio comprising over 4,000 commercialized formulations and a strong pipeline of more than 200 innovative products across 60+ dosage forms. Its influence extends well beyond India, delivering advanced healthcare solutions to global markets - underscoring a deep-rooted commitment to scientific excellence and continuous innovation. This capability is supported by world-class manufacturing facilities and advanced R&D centers, all equipped with state-of-the-art technology and cutting-edge infrastructure. These centers serve as the backbone of Akums' agility in responding to the rapidly evolving needs of the pharmaceutical industry.

At the core of its innovation engine is a team of skilled scientists and researchers dedicated to the development of novel drug delivery systems, the optimization of existing formulations, and the exploration of new therapeutic frontiers. Their expertise ensures that Akums not only keeps pace with global industry trends but actively sets new standards in pharmaceutical development.

By pushing the boundaries of traditional manufacturing and embracing next-generation scientific approaches, Akums continues to redefine possibilities in healthcare. Its innovations aim to improve patient outcomes, enhance treatment experiences, and expand access to advanced therapies—reinforcing the company’s position as a global frontrunner in pharmaceutical manufacturing and research.

Building a Future Ready Enterprise

In a sector where precision, product quality, and innovation are essential to maintaining a resilient healthcare ecosystem, Akums Drugs has firmly embedded technology at the core of its operations. The company’s tech-driven strategy spans every functional area - from human resources and manufacturing to

supply chain management and quality assurancedelivering enhanced efficiency, transparency, and scalability. Akums leverages advanced digital platforms such as LIMS for real-time quality monitoring and Ample Logic for a robust, integrated Quality Management System. Its proprietary Single-Window System (SWS) streamlines both capital and operational expenditures, enabling faster, data-driven decision-making and improved organizational agility. In an era defined by scientific acceleration, evolving regulatory demands, and increasing patient needs, Akums demonstrates that technology is no longer optional - it's imperative.

Innovation at Akums extends far beyond the production

floor. Biometric and facial recognition systems drive workforce efficiency, while a cloud-hosted data center provides secure, centralized access to critical business data. The company’s early adoption of SAP has ensured seamless cross-functional integration from the outset. Technology also drives Akums planning and packaging functions. Advanced digital tools support optimized production planning, while Harmony software enhances both precision and creativity in packaging design. By embedding intelligent technologies across every layer of its operations, Akums not only meets the highest global standards but cultivates a culture of agility, innovation, and continuous improvement - cementing its position as a future-ready leader in pharmaceutical manufacturing.

Digital Transformation and Sustainability

Akums Drugs & Pharmaceuticals Limited is spearheading a digital transformation that enhances productivity while strengthening its commitment to environmental sustainability. Through regular audits and ongoing improvements in energy-saving practices, along with the treatment of wastewater via Sewage Treatment Plants (STP) and Effluent Treatment Plants (ETP) across its manufacturing facilities, the company has achieved significant reductions in both energy and water consumption. Since its inception, Akums has aligned its operations with global Environmental, Social, and Governance (ESG) standards, embracing green initiatives such as native tree plantations, renewable energy adoption, energy-efficient infrastructure, and water recycling systems. These efforts underscore Akums’ dedication to sustainable and responsible growth.

Serving over 1,500 pharmaceutical companies across India and exporting to more than 60 countriesincluding highly regulated markets - Akums has

established itself as a trusted partner for pharmaceutical giants. Its technology-led manufacturing excellence and stringent compliance protocols position the company as a preferred choice for those seeking reliable outsourcing solutions that meet international quality standards. As the Indian pharmaceutical sector becomes increasingly complex and globally relevant, Akums is more than just a manufacturing partner - it is a technological enabler of healthcare innovation. Through continued investment in cutting-edge technologies, research and development, and world-class quality systems, Akums has earned its place as a technology leader in the industry, consistently setting new benchmarks.

At its core, Akums represents more than pharmaceutical expertise - it embodies a legacy of technology, innovation, and continuous progress. Since its foundation, the company has remained committed to improving lives, generating employment opportunities, and making a meaningful contribution to the community beyond commercial success.

DeepTech Index Report 2025

The Future is Now

Tracking Innovation Across Quantum, Agentic AI, Advanced Materials, SpaceTech & Beyond

The global deeptech market is accelerating towards a transformative phase, expected to surpass USD 715 billion by 2031 with a CAGR of over 48%. Powered by a convergence of AI, quantum computing, advanced materials, and biosciences, DeepTech is no longer just a frontier—it's the new core of national competitiveness and enterprise innovation. This report presents a comprehensive analysis of the 2025 landscape, covering trends, investment flows, technological breakthroughs, and India’s rising global role.

1. GLOBAL TRENDS & MARKET MOVEMENTS

1.1 Agentic AI & Autonomous Intelligence

• Rise of voice-first and context-aware autonomous agents

•Enterprise adoption across HR, IT support, customer service, and supply chain

•Emergence of AI orchestration platforms for multimodal and agentic workflows

1.2 Hardware-Led Innovation Surge

•Explosion in demand for 3D chips, quantum processors, neuromorphic hardware

•VC investment in deep hardware doubled YoY; 40% of funding flows into semiconductors and energy-efficient compute platforms

1.3 Quantum Technology Commercialization

•Shift from theoretical to applied quantum (secure communications, logistics modeling, crypto)

•Governments allocating billions to post-quantum cryptography and secure national data infrastructure

1.4 Bioengineering and Neurotechnology

•Integration of neural interfaces, AI-based drug discovery, and smart biosensors

•Biotech-DeepTech convergence becoming foundational to healthcare

1.5 Advanced Materials and Energy Tech

•Graphene and nanotech enhancing EVs, aerospace, and sustainability solutions

•Next-gen energy storage and photonic computing to power edge AI devices

1.6 Spacetech & Aerospace Intelligence

•India, US, and EU leading LEO satellite deployments

•Reusable propulsion, AI-powered mission systems, and precision agriculture via satellite

2. India DeepTech Ecosystem: 2025 Snapshot

2.1 Growth Metrics

•3,600+ active deeptech startups, 40% YoY growth

•Funding in Q1 2025 exceeded $324M in 35+ deals

•Tier II/III innovation hubs contributing ~45% of startup growth

2.2 Key Enablers

•National Deep Tech Startup Policy (NDTSIP) implemented

•Public-private innovation clusters around IISc, IIT-M, IISER, BITS

•Capital access through SIDBI, DPIIT, and sectoral innovation funds

2.3 Strategic Sectors

•Agentic AI for governance, defense, and citizen services

•Semiconductor design and fabrication (linked to India Semiconductor Mission)

•AgriTech, HealthTech, and CleanTech as priority verticals

4. Strategic Recommendations

For Enterprises & CXOs

•Begin pilot programs in Agentic AI & Quantum workflows

•Adopt edge AI + low-latency architectures in manufacturing

•Establish DeepTech R&D alliances with academia

For Policy Makers & Academia

•Expand R&D credit and IP transition schemes

•Create Tier II innovation superclusters

•Strengthen open data policies to power public AI agents

5 The Outlook for 2025–2030

For Investors & VCs

•Focus on hardware-centric and IP-rich startups

•Back teams working on sovereign tech infrastructure (chips, cloud, crypto)

•Explore biotech + AI convergence opportunities

By 2030, DeepTech will anchor not only digital economies but national resilience and autonomy. With AI agents operating enterprise backbones, quantum enabling secure global networks, and biological intelligence reshaping health systems - 2025 stands as the inflection point where India and the world are scripting the next era of civilization-scale innovation.

Report Contributors: Analysts from CXO TechBOT, EdgeSpark DeepTech Lab, and Frontier Intelligence.

THE TECH LENS

YOUR WEEKLY INSIGHT INTO TECHNOLOGY, INNOVATION & LEADERSHIP

Stay ahead of the curve with The Tech Lens – your curated source of the most impactful tech updates, tailored for CXOs, tech leaders, entrepreneurs, and AI enthusiasts navigating the ever-evolving digital landscape.

WHY SUBSCRIBE?

Each edition brings you: Breakthroughs in AI & Emerging Technologies

Insights on Enterprise

Innovation & Productivity Trends in Strategic Leadership & Decision-Making

Power-Packed Summaries

Delivered Every Saturday

Trusted by 25,000+ readers worldwide – including CIOs, founders, and digital transformation leaders.

Get your weekly deep dive – only from The Tech Lens For partnerships or sponsorships: Contact@cxotechbot.com

FROM MODELS TO AGENTS: RETHINKING GOVERNANCE FOR AUTONOMOUS AI SYSTEMS

“The real question is not whether machines think, but whether men do.”

– B.F. Skinner

Imagine this:

You’ve hired a brilliant analyst. Initially, they simply run reports on request. But over time, they start anticipating questions, uncovering patterns, and making decisions—without asking. One day, they reroute a shipment, adjust pricing, or send a note to a client. Not because you asked, but because they thought it was the right thing to do.

Now imagine that an analyst is an AI.

This isn’t science fiction. This is where we are today. Welcome to the agentic era—where artificial intelligence doesn’t just respond to instructions but acts with intent.

The Quiet Revolution: From Automation to Autonomy

Until recently, AI systems functioned like calculators on steroids. They were highly capable, data-hungry engines designed to predict outcomes, classify content, or recommend actions. We called them models—and they waited patiently for prompts.

We were busy tuning models. Accuracy, loss functions, optimization—these were the familiar coordinates of our AI universe. We built systems to predict, recommend, and assist. These systems were impressive, yes—but fundamentally reactive. They waited for a prompt, a command, a dataset. They didn’t act on their own.

Today, that’s changing. Rapidly.

But today, with the convergence of large language models, planning architectures, APIs, and memory loops, we’re witnessing the rise of something fundamentally different: agents. These are AI systems capable of initiating tasks, navigating tools, making decisions across steps, and continuously adapting their actions based on outcomes.

We’re entering the agentic era of AI—one where systems are no longer just trained models but are evolving into autonomous agents. These agents can

take goals, interpret environments, make decisions, and trigger actions—often without human intervention. They’re not just tools. They’re becoming actors.

A model answers a question.

An agent finds the question, answers it, books a meeting, writes the email, and logs the interaction in your CRM. Welcome to the agentic era—where artificial intelligence doesn’t just respond to instructions but acts with intent.

It’s a profound leap—from passive intelligence to proactive agency.

And this leap changes everything we thought we knew about AI governance.

This shift challenges one of the core assumptions of how we’ve governed AI so far: that we, the humans, are always in charge.

AI governance has traditionally been structured around three pillars:

•Data integrity: Are the inputs ethical, diverse, and high-quality?

•Model accountability: Can we explain its behaviour?

•Compliance checks: Does it align with laws and organizational policies?

These frameworks worked reasonably well—when the system was static. You could validate a model before deployment, lock its parameters, monitor its outcomes, and move on.

But agents break this mold.

They learn across interactions. They initiate actions on your behalf. They collaborate with other agents. They even reinterpret their original goals based on evolving contexts.

In short: they behave.

And governance rooted in frozen snapshots is ill-suited for a moving system.

“Change the way you look at things and the things you look at change.” – Wayne Dyer

Governance in the agentic era must be dynamic, context-aware, and intervention-ready. We're no longer designing systems that perform calculations—we're shaping systems that can exercise judgment.

What Does It Mean to Move from Models to Agents?

Let’s simplify it.

If AI models are like GPS devices—they give you directions when asked—then agents are more like autonomous vehicles. You tell them the destination, and they decide how to get there. Sometimes they’ll ask you for help; sometimes they won’t. Sometimes they’ll reroute entirely based on real-time information.

And just like autonomous vehicles, autonomous AI agents introduce a new kind of complexity:

How do we stay in control of a system that makes its own choices?

The AI systems we’re deploying today don’t just complete sentences or classify images. They initiate email sequences, manage supply chains, detect fraud, optimize pricing, write code, conduct research, even handle customer conversations. More importantly, they do this across steps—reasoning, planning, acting.

In other words: agency.

The implications for governance are not evolutionary. They are transformational.

The Shift: Governance as Guardrails, Not Just Rules

“Change the way you look at things and the things you look at change.” – Wayne Dyer

Traditional AI governance is designed for supervised predictability. Checklists, model validations, data audits, fairness assessments—these worked well when AI stayed within the boundaries we defined.

But agents don’t operate within boundaries. They explore them.

The shift from governing models to governing agency calls for a new approach—one that’s dynamic, contextual, and continuously learning. It’s no longer enough to ask: Is the model fair? Is it explainable? Now, we must ask:

•What decisions is the agent authorized to make?

•What is its scope of autonomy?

•How is it supervised—and by whom (or by what)?

•How does it handle unforeseen scenarios?

•Can it explain its chain of reasoning across decisions?

•What happens when multiple agents interact or conflict?

We’re not just auditing outcomes anymore—we’re trying to understand intentions and behaviors within autonomous systems.

This introduces a deeply human challenge: how do we encode judgment into systems that learn beyond our visibility?

Where This Matters: From Boardrooms to Frontlines

We’re moving from automation to delegation. Automation is about efficiency—rules, repeatability, control.

Delegation is about trust—intent, autonomy, responsibility.

When we delegate to a human, we expect them to improvise, learn, and decide—but also to explain themselves, stay aligned with values, and escalate when needed.

That’s exactly the bar we now need for AI agents.

So we must ask new governance questions:

•What is the agent authorized to decide?

• How do we constrain its context without stifling creativity?

• Can it identify and resolve conflicts in multi-agent environments?

• How do we ensure it acts in a way that reflects organizational values, not just optimization functions?

•And most importantly: How do we know when it’s gone off-track—before the damage is done?

These aren’t philosophical curiosities. They’re boardroom-level concerns.

Whether you lead a team, a company, or a product line, the implications are already here.

• In finance, autonomous agents are managing portfolios and fraud detection in real time. But who oversees the overseer?

•In marketing, agents are personalizing campaigns and managing interactions. How do we ensure brand integrity when the agent speaks in our voice?

•In operations, agents are optimizing logistics and inventory. What happens when they prioritize efficiency over resilience?

This isn’t theoretical.

Last year, an enterprise chatbot acting as a “customer success agent” offered unexpected discounts to customers. The logic made sense to the agent—it was optimizing for retention—but it wasn’t aligned with business policy. The root cause? No clear policy sandbox defining the boundaries of agency. These are not just technical problems. They’re governance failures.

We need new roles and tools: AI behavior monitors, simulation environments, autonomy thresholds, escalation protocols. And perhaps most importantly, cross-functional governance frameworks that bring together technologists, ethicists, business leaders, and legal experts.

A Reflection: Are We Governing Intelligence, or Delegating It?

“We do not see things as they are, we see them as we are.” – Anaïs Nin

In many ways, AI governance is not just about AI. It’s a mirror reflecting our own blind spots, values, and assumptions about control.

Moving from models to agents forces us to re-examine what it means to delegate decision-making. Not just to people, but to systems. And in that shift lies both potential and peril.

We are no longer merely building tools—we are shaping digital actors. Our responsibility, then, is not just to monitor their performance but to question their purpose, their boundaries, and their alignment.

So here’s a question worth sitting with:

Are we preparing our governance systems to match the autonomy of our AI systems—or are we still trying to control tomorrow’s intelligence with yesterday’s rules?

A New Governance Playbook: Guiding Agency Without Stifling It

So, what does governance look like in the agentic age? Here’s a starter framework:

• Autonomy Thresholds: Define the boundaries within which agents can make decisions. What can they decide alone? What needs review?

•Behavioral Monitoring: Use simulations and sandbox environments to test agent decision-making before deployment.

•Transparent Memory: Enable human review of the agent’s reasoning process—what it did, why, and when.

•Fail-Safe Escalation: Build interruption protocols. Just like a junior employee knows when to check in, so should an agent.

•Multi-Stakeholder Oversight: Governance isn’t just IT’s job. It must involve legal, compliance, product, and customer experience leads.

This isn't just about minimizing risk. It's about building confidence in collaboration—between humans and intelligent systems.

For decades, AI has been backstage—running calculations, analyzing data, suggesting decisions.

Now, it’s stepping onto the main stage—making choices, taking initiative, representing us.And just like with any empowered team member, we must provide not just instructions, but guidance. Not just constraints, but context. Not just oversight, but shared understanding.

“A mind that is stretched by a new idea never returns to its original size.” – Oliver Wendell Holmes

Governance in the age of agents is not about pulling AI back into predictability. It’s about evolving our systems, our culture, and our leadership to govern agency wisely.

Pranav Kumar

Senior Director(Data & AI) Capgemini

Because the question is no longer can AI act?

It’s: Can we govern the world where it already does?

The agentic era is stretching our collective imagination—and our governance playbooks. As we walk this path, we’ll need more than compliance checklists. We’ll need wisdom, collaboration, and courage.

Because governing agencies aren't just about AI. It’s about us.

Let’s keep this conversation alive. How is your organization thinking about AI agents and governance? Where do you see the biggest gaps—or opportunities?

Pranav Kumar is a distinguished Digital, Data & AI Business Leader with over 20 years of global experience at the convergence of consulting, product innovation, and digital services. He partners with Fortune 500 companies to deliver data-driven customer experiences by seamlessly integrating technology, people, and platforms.

His deep expertise spans composable and packaged CDPs, Adobe and Salesforce ecosystems, conversational AI, and hyper-scaler solutions. A trusted advisor to CXOs, Pranav has led large-scale digital transformation programs that unlock growth and deliver strategic impact across complex, multicultural markets.

Passionate about innovation and the startup ecosystem, he actively mentors entrepreneurs and global business school graduates. He contributes to national innovation platforms such as the Atal Innovation Mission (NITI Aayog) and Technovation. Known for his strategic foresight and human-centered leadership, Pranav also serves as a keynote speaker, DE&I advocate, and advisory board member, championing inclusive innovation and future-forward thinking.

BLOOD BRAIN BARRIER

Transient Disruption Of by Loud Sound And Vibrations

And Its Impact on Cerebral Homeostasis

Of the 7.9 billion global population in 2021, more than 3 billion people worldwide (over 1 in 3 people) lived with a neurological condition. Neurological disorders are the leading cause of illness & disability worldwide. This article discusses the impact of high pitch loud noise and vibrations on Blood Brain Barrier (BBB) plasticity and manifestation of neurological disease conditions.

The noise standard for mentally stressful tasks is 55 dB. If the noise source is continuous, the threshold level is <55 dB. Accordingly, the sound of >55 dB is considered as noise pollution. The National Institute for Safety & Health (NIOSH) recommends not more than an 8-hour exposure limit of 85 dBA. Per their recommendation, a hearing conservation program should be in place if a worker is exposed to 85 dB x 8-hr work period. Further, if the noise level is 95 dB, the worker can be exposed to the noise for only 4 hrs over a work shift. Extended exposure to noise >90dB triggers stress response. The sound at open air musical concerts peaks >100 dB, which is generally considered unsafe for exposures exceeding 15 min. Exposure to sound at the hearing threshold level for extended periods alters neural activity in auditory processing, emotional and vascular autonomic control regions of the brain. The implosive oscillations caused by acoustic emissions generate shock waves that perforate the weak regions of the BBB near to the lining of the circumventricular organs.

Also, the high pitch sound or vibration causes oxidative stress, which triggers an inflammatory response resulting in loss of BBB integrity. Exposure to sound above 70 dB intensity for long intervals, can cause damage to right frontal cortex histology, cerebral ultrastructure, and BBB, thus allowing blood borne substances to pass across the BBB into the brain tissue. The persistent high pitch noise causes alterations in neurotransmitter release, affects synaptic plasticity, leading to learning and memory impairment.

The mobile phones use wireless technology, with the majority of them operating in a frequency range of about 900 - 1800 MHz, pulse frequency of 217 Hz, pulse width of 577 s, and duty cycle of 12.5%. Only

recently has the frequency risen above 2100 MHz.

about 900 - 1800 MHz, pulse frequency of 217 Hz, pulse width of 577 s, and duty cycle of 12.5% [15]. Only recently has the frequency risen above 2100 MHz [16].

Nitric oxide activity and tumour necrotic factor level increase in the brain tissue after exposure to multi-transceiver mobile phones for extended durations. This relatively selective effect on the cardiovascular and nervous system is because of the high metabolic rate and lipid composition, respectively, which renders them sensitive for oxidative stress response to electromagnetic field exposure during both physiological and pathological processes, such as anxiety, hypertension, and neurodegeneration.

This review discusses the blood brain barrier architecture, function and its disruption by loud sound and phone ring tones or vibrations.

The Blood Brain Barrier

The BBB barrier is a selectively permeable membrane that separates the bloodstream from the brain and flush the metabolites and ions from the brain tissue to blood. Active efflux pumps out the brain materials by ATP binding cassette (ABC) transporters for example P-glycoprotein and Breast Cancer Resistance Protein. A crucial interface between the vascular system and the brain, the BBB acts as a filter to protect neurons from pathogens and inflammation. While it guards the neural tissue from exposure to xenobiotics, it also poses hindrance to treat neurological diseases by limiting the permeability of drugs, and thus achieving therapeutically effective concentration in the affected brain tissue/region. The BBB is composed of endothelial cells (ECs), pericytes and astrocytes. therapeutically effective concentration in the affected brain tissue/region. The BBB is composed of endothelial cells (ECs), pericytes and astrocytes.

ECs form the walls of the blood vessels and impart mechanical stability. They are connected by tight junctions (TJs) and adherens junctions (AJs).

TJs are on the apical (lumen side) part of the cell, conjoined to the AJs. TJs regulate the passage of solutes between cells and restrict the diffusion of membrane proteins between the apical and basal cell surfaces.

TJs, the primary regulators of BBB permeability, are formed by three types of transmembrane proteins i.e. 60-kDa integral membrane protein “Occludin”, 20–24/27 kDa “Claudins”, and Junctional Adhesion Molecules (JAMs). Occluding regulated permeability of TJs and Claudin link the membranes of adjacent cells. TJs are anchored to the actin cytoskeleton via cytoplasmic scaffolding protein Zonula Occludens-1, 2 and 3 and heterotrimeric G-proteins.

The high trans-endothelial electrical resistance (TEER) is due to limited paracellular transport governed by tight junctions (TJs). TJs limit passive diffusion through the paracellular space, primarily allowing the lipophilic molecules with specific characteristics and molecular weight cutoff of ≤450 Da to pass through.

By interacting with the cytoskeleton, AJs link ECs to form continuous sheets. AJs are formed by the homophilic interactions between transmembrane cadherin and intracellular catenin proteins to anchor them to actin filaments and tubulin microtubules.

Cadherins and catenins mediate pericyte interactions and maintain barrier integrity. Cadherin-10 is predominantly expressed in brain microvessels with BBB phenotypes, while VE cadherin is more abundant in larger pial vessels and in relatively leaky barriers. During acoustic stimulation, the bonds between TJ and AJ proteins are disrupted and decoupled, resulting in transient and reversible opening of the BBB.

To facilitate blood-parenchyma exchange, ECs express receptors and transporters. The large molecules are transported through endocytosis, encapsulating them in caveolin-lined vesicles. This can be specific i.e., receptor-mediated (RMT) or non-specific i.e., adsorption-mediated (AMT) transcytosis. Two common proteins involved in RMT are LDL-receptor related protein-1 and the receptor for advanced glycation end-products (RAGE).

Partially enveloping ECs, the pericytes stay embedded within the vascular basement membrane and regulate the EC development and physiology through intercellular signalling mechanisms. Pericytes extend long membrane processes across the abluminal side of capillaries and cover about 22–37% of the EC surface. Pericytes regulate angiogenesis, infiltration of immune cells and deposit extracellular matrix components.

Astrocytes further encapsulate blood vessels in the brain, extending their end-feet over 99% of the endothelial surface. Astrocytes secrete their own parenchymal basement membrane “glia limitans” in the perivascular space. Astrocytes regulate electrochemical activity, the innate immunity and balance parenchymal water and metabolites.

Transient disruption of Blood Brain Barrier

Under normal circumstances, a small number of mononuclear leukocytes, monocytes and macrophages may enter the CNS via diapedesis. This low intensity leukocyte trafficking across the BBB is for immune surveillance and to exert response to brain infection. The barrier function, however, is not always rigid and BBB undergoes modulation and regulation, both physiologically and pathologically. The barrier disruption can range from mild and transient TJ opening to chronic barrier breakdown.

Pericytes maintain the integrity of the B-B and their depletion increases BBB permeability via upregulation of endothelial transcytosis. Astrocytes promote BBB formation and integrity via the Hedgehog signalling pathway.

Destabilization of BBB increases the risk of stroke and neurodegenerative diseases, for example vascular dementia. A multitude of factors can disrupt the BBB, which include secreted elements to immune cells and pathogens, reactive oxygen species (ROS), activation of MMPs, and chronic up-regulation of angiogenic factors and pro-inflammatory cytokines. Immunoglobulin G (IgG) extravasation is commonly used as an index of BBB disruption.

Augmentation of paracellular transport relies on weakening the TJ/AJ and allowing inter EC passage. Enhanced paracellular permeation can be achieved by chemical or physical mechanisms. Vasoactive chemical compounds such as histamine, bradykinin, alkylglycerols, tumour necrosis factor, or interferon-γ

activate signalling pathways within ECs and increase BBB permeability. Alternative approaches include infusing hyperosmolar agents such as mannitol to reduce endothelial intracellular volume and open the BBB. The flip side to the chemical approach is that it often produces off-target effects causing widespread tissue damage, thus limiting their clinical application. The controlled opening of the BBB has also been demonstrated using biomolecules like antibodies or peptides, which interact with the claudins. Claudin-5 antibody, for example, enhances drug penetration into the BBB.

BBB disruption by noise

In a 6-week multi-transceiver mobile phone electromagnetic field, vibration and ringtone exposure trial conducted on rats, a significant increase in BBB permeability (as estimated by permeation of Evans Blue dye) in the cerebellum, cerebrum, and the two hemispheres of the brain was noticed along with increase in the TNFα levels in brain. Evans blue dye uptake was more prominent in the right cerebrum, and right cerebellum. Evans Blue dye (960da) has high affinity to plasma albumin. 12 molecules of albumin bind to one molecule of Evans blue. The Evans Blue-Albumin complex (68 Kda) is too big to cross BBB. Therefore, in a normal permeability scenario, the neural tissue remains unstained with Evans blue, However, if BBB is disrupted, the brain tissue gets stained by Evans blue.

However, if BBB is disrupted, the brain tissue gets stained by Evans blue.

The BBB became permeable to the Evans Blue Albumin Complex (68.5 kDa), when the mice were made to hear the song of the scorpions ‘Still Loving You’ for 2 h at 100 dB and 370 Hz intensity. The opening of BBB was reversible and mediated through stress-mediated TJ machinery disorganization. Additionally, the plasma epinephrine level increased significantly and restored to basal level only after 24hrs. The loud sound causes a transient increase in stress hormone “epinephrine” in the plasma by approx. 3-folds. Epinephrine decreases cerebral blood flow by 33 ± 5% due to vasorelaxation and decreased vascular tone.

Spatial learning and memory are coordinated mainly by the hippocampus. Exposure of rats to 100dB noise for 4hr/day x 30 days impairs working and reference memory. and produces excessive free radicals (ROS), disrupting the normal cellular functions and integrity. The imbalance of oxidative status in hippocampus and cerebellum, two key regions involved in memory processing, has been observed in rats exposed to 95–97 dB sound for 2 hrs. Sprague Dawley rats when exposed to 100dB sound daily for 2 hrs over a period of one month exhibited reduction in conceptual abilities, attention deficit and amnesia. Elevated levels of inflammatory cytokines like TNF-α, IL-6, IL-1α and IFN-γ were observed in hippocampus and plasma. The spatial learning and memory were thus critically affected. Also, the pyknotic and apoptotic neurons numbers increased in CA1, CA3 and dentate gyrus regions coupled with the increase in hippocampal DNA fragmentation, as confirmed by TUNEL assay. The inflammatory genes like CCL2, CCR5, IFN-γ, IL13, IL1A and TNF-α were upregulated and bone morphogenetic protein-2 and IL3 genes were downregulated.

Repeated loud noise exposure has been shown to alter stress hormones and impair cognition. It also induces metabolic and structural changes in neurons, increases acetylcholinesterase activity, elevate plasma corticosterone level, reduce the dendritic count in hippocampus and medial prefrontal cortex regions and

cause impairment of spatial memory in rats. A chemical macromolecule “Dextran” (75 Kda) made its way into the brain of 2-month-old mice when they were made to hear audible sound at 110 dB and 370 Hz in a 60-s on/off pattern for 2 hrs.

Modulation of the apoptotic pathway via increase in Pro-apoptotic protein caspase-3 has been observed in the hippocampus of rats exposed to loud noise. The impulse noise of 198-202 dB caused focal ischemia in rat anterior cortex, hippocampus, thalamus and cerebellum and impaired cognition and spatial memory. Structural and functional issues were noticed

BBB disruption by vibration

In humans, regiospecific exposures to vibrations have been proposed as a curative approach in physiotherapy centres and whole-body vibration (WBV) via massage chairs commonly practiced in gyms for muscle relaxation and toning after extreme physical activity. Vibration is sensed by tactile receptors in the outer skin (Merkel disks—sensing vibratory strength and responding to 5–15 Hz), inner skin (Meisner corpuscles—sensing vibratory frequency and responding to 20–50 Hz), and in deeper tissues (Pacinian corpuscles—sensing acceleration and responding to 60–400 Hz). Audible sound frequency ranges from 20Hz - 20,000Hz and Ultrasonic waves Frequency is>20 kHz. 0–250 Hz vibration may be considered as “low frequency” and >250 Hz as “high frequency”.

WBV serves as a countermeasure against cardiovascular alterations due to aging and obesity, as it enhances vasodilation of small arterioles, and possibly capillaries in human leg muscles.

BBB permeability is sensitive to prolonged external accelerations. Vibration results in stimulation of ECs, which in turn increases endothelial nitric oxide synthase (eNOS) activity and releases nitric oxide (NO) and adrenomedullin. NO regulates blood flow and vascular tone by affecting the vascular smooth muscle with the activation of the enzyme guanylate cyclase (sGC) and the phosphorylation of extracellular signal

regulated kinase (ERK1/2).

Endothelial cells mechanosensor-proteins, Syndecan-4 (Syn4) vascular endothelial growth factor (VEGF), and Krüppel-like Factor 2 (KLF2) translate the physical force from the vibration into biochemical signals. A significant induction of IgG extravasation in hippocampal parenchyma was observed in 2–4-month-old male C57BL/6J mice, when exposed to 2 × g vibrations for 63 consecutive days.

Vestibulo-sympathetic alteration, nature of stress, vascular status and metabolism may have acted synergistically augmenting the BBB permeability.

AUM chanting vibrations

“AUM” or “OM” Chanting vibrations impact both the mind and body. AUM chanting is widely considered as a cue to relaxation. When performed in a large group, AUM chanting vibrations are loud and of higher intensity. During effective AUM chanting the vibration sensation is experienced in the head and around the ears. This sensation is believed to be transmitted through the auricular branch of the vagus nerve. AUM chanting, therefore, has been reported to mediate the effect via vagus nerve stimulation.

The vagus nerve, one of the 12 cranial nerves, is a major parasympathetic (efferent) component of the autonomic nervous system and transmits sensory information from brain to the body. It regulates cardiac and gastrointestinal function, in muscle control of mouth and throat, in the neuroendocrine- immune system, and in the regulation of emotion including anxiety and depression. Vagus nerve stimulation (VNS) is a recognized practice commonly done with manual massage or compression, electrical stimulation, or vibration including with the voice or gargling throat or with external vibrotactile devices.

Using functional Magnetic Resonance Imaging (fMRI), the neurohemodynamic correlates of audible 'OM' chanting were examined in healthy volunteers (n=12; nine men). Significant deactivation was observed bilaterally during 'OM' chanting in comparison to the resting brain state in bilateral orbitofrontal, anterior

cingulate, parahippocampal gyri, thalami and hippocampi. The right amygdala too demonstrated significant deactivation.

The neurohemodynamic correlates of 'OM' chanting indicate limbic deactivation. The limbic system is the part of the brain involved in our behavioural and emotional responses, limbic system buried deep within the brain, underneath the cerebral cortex and above the brainstem. The two major structures of the limbic system are the hippocampus and the amygdala. No significant activation was observed during 'OM' chanting. It thus needs to be carefully assessed if said effects are mediated by “AUM” chanting driven transient BBB disruption.

Hippocampal BBB is progressively compromised with age and cognitive decline. It therefore needs due caution for aged people to participate in solo or group chanting because if a 66Kda macromolecule like albumin can get in the brain, many large molecular weight substances from the blood can also. These (otherwise impermeable) substances can severely affect microglia, the cells regulating brain development, neuronal networks, and injury repair.

Take home

BBB plasticity shields the brain tissue from blood borne substances. If compromised, it may result in severe neurological manifestations. The manifestation though may not be acute, esp in young adults, owing to the brain defence mechanisms, for example active efflux pumps, limited diffusion and Cytochrome P450 (CYP) mediated metabolism. So, a major chunk of the substances which make way into the brain due to BBB disruption can be metabolized or effluxed back into the systemic circulation. In case if they stay back in the brain tissue, they largely exert only mild focal effects as the diffusion in brain tissue is severely curtailed. Further, the disruption is reversible, and the plasticity is slowly restored after the sound or vibration source is withdrawn. However, if the person who is stressed/depressed, in state of fear or anxiety having elevated epinephrine levels or having some systemic inflammation/infection or if under the medications or

having circulating tumour cells, when exposed to loud noise for prolonged period, the effect of extravasation is profound Earpods/Airpods exert combined effect of sound and high vibration and are thus more likely to cause BBB disruption. The snug fit earpods/airpods if used for an extended period of time for listening to loud music may cause disruption of BBB and influx of blood borne substances.

It is important to mention here that laboratory rat and mice are very sensitive to sound, and it needs to be assessed whether the extent of BBB disruption and neurological manifestations observed in laboratory rodents is translatable to humans.

AUM chanting often precedes meditation sessions to achieve a calm composure state swiftly. The 'A' in AUM is pronounced short and “UM” is extended/stretched to create maximal possible spinal and cranial vibration. The state of composed demeanor attained via AUM chanting if driven by transient disruption of BBB and influx of blood borne molecules could really be concerning especially if the person is on medication or having systemic infection or inflammation. If mediated by BBB disruption, it could then be potentially an unhealthy approach to achieve a stress-free and peaceful state. Silent meditation could thus be more beneficial than loud chanting.

Similarly, the loud sound of bells in religious places may be creating shock waves to disrupt the BBB. The vibrational sounds emanating from the temple bells generate a ripple effect which may disrupt the tight junctions of BBB and augment the influx of the blood borne substances which eventually may result in diminished distraction and cognition. The bells thus may be reducing the brain hyperactivity and attention deficit by transient disruption of BBB and exposure of the brain to blood borne substances.

Dr. Satinder Singh Associate Director (DMPK) Aragen Life Sciences Private Limited

Dr. Satinder Singh is an adept professional in the field of pharmaceutical research and development. He boasts over 16 years of comprehensive experience across diverse domains including drug discovery, vaccine research, molecular pharmacology, and formulation R&D. With a rich background spanning roles such as Research Associate at ZRC, Dr. Satinder Singh demonstrated proficiency in therapeutic areas and disease pathologies. His adeptness at multitasking, flexibility in assuming various roles, and resilience in problem-solving have been instrumental in his success. Dr. Singh's commitment to continuous growth led him to his current position as Assistant Manager R&D (IPR) at IPCA. Here he continues to push boundaries and explore new challenges.

Neurotechnology and Brain-Computer Interfaces: The Future of Cognitive Health

In recent years, neurotechnology and brain-computer interfaces (BCIs) have moved from the fringes of neuroscience and futurism into the heart of technological innovation and biomedical research. Once confined to laboratories and speculative fiction, these technologies are now shaping the future of cognitive health, neurorehabilitation, and human augmentation. As we enter a new era where machines can decode, influence, and even enhance brain activity, the ethical, scientific, and policy implications are profound.

Understanding Neurotechnology and BCIs

At its core, neurotechnology refers to tools and systems that interact directly with the nervous system. These include electrical, chemical, or optical devices that can monitor, stimulate, or modulate neural activity. Brain-Computer Interfaces (BCIs) are a key subset—systems that establish a direct communication pathway between the brain and an external device, often bypassing traditional neuromuscular output.

BCIs are broadly categorized into invasive, partially invasive, and non-invasive types. Invasive BCIs, like those being developed by Neuralink and Synchron, involve implanting electrodes directly into brain tissue, offering high fidelity but with surgical risks. Non-invasive solutions, like EEG-based headsets, are more accessible but often suffer from lower resolution and signal interference.

Applications in Cognitive Health: Where Promise Meets Reality

1. Neurorehabilitation and Recovery

BCIs are already proving transformative in neurorehabilitation. Stroke patients and those with spinal cord injuries can regain motor control through neurofeedback and assistive neuroprosthetics. Systems can decode motor intention from neural signals and translate them into movements via robotic limbs or exoskeletons, retraining the brain in the process. The brain plasticity harnessed through these feedback loops holds immense promise for reversing cognitive and motor impairments.

2. Early Diagnosis and Monitoring of Neurodegenerative Diseases

Conditions like Alzheimer’s, Parkinson’s, and ALS may soon be diagnosed far earlier using neurotechnological biomarkers. Machine learning models trained on longitudinal brainwave data are beginning to identify patterns of cognitive decline before they manifest behaviorally. The ability to detect preclinical neurological deterioration will radically change how we manage aging populations.

3. Cognitive Enhancement and Memory Augmentation

Perhaps the most controversial application of neurotechnology lies in cognitive enhancement. Experiments with transcranial direct current stimulation (tDCS) and deep brain stimulation (DBS) have shown potential to enhance memory, attention, and executive

functioning. While current results are mixed and largely confined to research contexts, the notion of neural augmentation is gaining traction, especially in high-performance fields like military training and aviation.

4. Mental Health and Emotional Regulation

Wearable BCIs combined with AI-based mental health platforms can monitor brain states associated with stress, anxiety, and depression. Real-time interventions—ranging from personalized mindfulness routines to neurostimulation—can provide relief without pharmacological side effects. Closed-loop neurostimulation, where devices respond dynamically to brain signals, is a frontier for treating refractory depression and PTSD.

Neuroethics and the Need for Regulatory Frameworks

With great promise comes great peril. As neurotechnology progresses, neuroethics must evolve equally fast. Key issues include:

•Cognitive Liberty: Who owns your thoughts? What happens if brain data is hacked or commodified?v

•Privacy and Surveillance: Neural data is the most intimate kind of personal information. Its misuse could redefine surveillance capitalism.

•Equity of Access: Will neuroenhancement widen existing socio-economic inequalities? Could BCIs become tools of elitist augmentation?

•Consent and Autonomy: Especially in therapeutic contexts, how do we ensure informed, voluntary consent for technologies that modulate brain states?

International bodies such as the OECD and UNESCO have started framing guidelines for responsible neurotechnology use. However, regulation remains fragmented and largely reactive. Countries like Chile are pioneering “neurorights”, proposing that mental privacy and identity be protected as fundamental human rights—an approach that deserves global emulation.

The Future Trajectory: From Assistive to Integrative

We are at a transitional moment in the neurotech landscape. Initially developed to restore lost function, BCIs are rapidly moving toward augmentative and integrative roles. Imagine future scenarios where:

• Employees use non-invasive BCIs to boost focus during cognitively demanding tasks.

• Students access AI-curated knowledge streams through neural input systems.

• Artists co-create with generative neural tools by visualizing their thoughts directly into digital canvases.

Moreover, the convergence of neurotechnology with other DeepTech domains—such as AI, quantum computing, and biotechnology—could unlock exponential capabilities. AI algorithms can help decode vast neural signal datasets, while quantum sensors may offer unprecedented resolution in brain imaging.

Industry and Research Outlook

The neurotechnology market is projected to surpass $30 billion by 2030, driven by investments from healthcare giants, Big Tech players, and military R&D. Startups are innovating in fields like neurogaming, immersive education, and brainwave-driven IoT control systems. Research hubs across MIT, Stanford, and ETH Zurich are pioneering next-generation BCIs with adaptive, user-centered designs.

Key technical challenges remain—signal fidelity, biocompatibility, long-term stability of implants—but progress is accelerating. The move from experimental labs to consumer-grade neurotechnology is no longer a question of "if," but "when."

Conclusion: The Neurotechnological Turn in Human Futures

Neurotechnology and BCIs are not just medical tools—they are philosophical instruments challenging our notions of consciousness, agency, and selfhood. As we design technologies that can interpret and influence the brain, we must also reengineer the social, ethical, and policy architectures that govern their use.

If harnessed responsibly, neurotechnology holds the key to unlocking a future where cognitive health is not merely restored, but optimized. It offers a vision where mental illness is mitigated, neurodiversity is empowered, and the human mind becomes the central interface in a symphony of digital possibility.

The next frontier is not just artificial intelligence,it is augmented intelligence: the co-evolution of human cognition and machine capability. And neurotechnology is the bridge that will take us there.

FROM FOUNDER PITCHES TO BILLION-DOLLAR IPOS: LESSONS FROM ADVISING 400+ STARTUPS

When you’ve advised over 400 Startups and SMEs across 70+ countries, you get a front-row seat to the evolution of Technology and markets – It also gives you a unique perspective on how Markets and Technology are developing. I've witnessed industries shift, business models come and go, and capital cycles fluctuate. A different kind of founder, however, has surfaced in recent years; they are quiet, focused on research, and developing technologies that aren't popular on social media. The DeepTech entrepreneurs are these people.

DeepTech isn't about making quick money. Long-term planning and patient capital are key. Although it's still in its infancy, India has a lot of potential.

Consider the example of Quantum Computing. Around the world, the race is intensifying. In 2019, Google asserted that their Quantum machine had solved a problem that would have taken a traditional computer 10,000 years, in just 200 seconds. Despite ongoing discussions about Quantum supremacy, one thing is certain: a new paradigm is taking shape!

India is not sitting idle. With a budget of ₹6,000+ crore (about $730 million), the government started the

Tushar Kansal Founder & CEO Kansaltancy Ventures

National Quantum Mission in early 2023 with the goal of creating Quantum computers with up to 1,000 physical qubits by 2031. This involves leapfrogging rather than merely catching up to the West.

Actual research on photonic qubits, superconducting materials, and quantum sensors is underway at IIT Madras, IISER Pune, TIFR, and CDAC. The intention is present. What is missing is a more robust link between Laboratory research and Commercial implementation. VCs like me can help with that.

I've worked with Startups in the last year that are working on Hybrid Quantum-Classical algorithms for Pharmaceutical simulations, Quantum ML for Asset pricing, and Quantum-safe Cryptography. A Team from Bangalore is collaborating with foreign Labs to speed up Drug discovery by simulating Protein folding. For BFSI companies, another Pune-based Startup is developing Lattice-based Encryption solutions.

It's not your typical 12-month Product-Market-Fit (PMF) narrative. These are marathons that last ten years! And that calls for a different kind of Capital one that is patient, extremely technical, and prepared to withstand risks related to ecosystems and regulations.

Let's now discuss Semiconductors. The annual cost of India's reliance on imported chips exceeds $15 billion. And the dangers of that dependence were made clear by the Pandemic. The response from the Indian Government was prompt. The creation of a Fab ecosystem, partnerships with companies like TSMC and Micron, and the $10 billion Semiconductor incentive package are all positive moves.

Micron, for instance, is setting up a $2.75 billion assembly and testing plant in Gujarat, expected to create over 5,000 direct jobs. This is more than a factory. It’s an Anchor around which design and fabrication Startups can cluster.

chips for IoT and specialized processors for automotive and drones. One Delhi-based Startup has developed an ultra-low power RISC-V based chipset designed for wearable healthcare devices. They’re already talking to Taiwanese foundries for manufacturing.

But Semiconductors are not just about Fabs. They’re about design, supply chains, IP protection, and scale. We need Indian VCs to understand these nuances. Most importantly, we need to look beyond short-term exits - National security, Energy independence and Strategic leverage are at stake.

Artificial Intelligence is another area of rising activity. But we must move beyond ChatBot clones. The real Gold lies in sector-specific AI solutions. Startups in India are now building LLMs trained on Legal, Medical and Agricultural datasets. These vertical LLMs are leaner, cheaper, and far more useful than general-purpose models. Some time ago, the CEO of TCS was asked when will TCS build LLM’s in Indian vernacular languages – he replied that it is too costly and not required! But the Indian Government stepped in and has chosen Sarvam AI as the Startup which will build our own LLM!

In AgriTech, a Hyderabad-based Startup is using Satellite imagery and AI to predict Crop Health and Irrigation needs with 85%+ accuracy. This isn’t glamorous Tech, but it’s transforming the economics of farming.

My extensive association with Entrepreneurship-Development Cells at IIT’s, including at Delhi, Mumbai, Chennai, Lucknow and Ropar, has made me see first-hand, the focus with which India’s Startups are building the future of Tech!

Design-linked incentives (DLI) are encouraging Fabless startups. A few I’ve evaluated are working on Analog

On the Edge computing side, a Mumbai Startup is building on-device AI accelerators for smart CCTV cameras, enabling real-time threat detection without cloud dependency. It’s an excellent example of solving for Indian infrastructure constraints!

Then there’s Energy Tech. India added 15 GW of renewable capacity in 2023 alone, and the government has committed to 500 GW of non-fossil fuel capacity by 2030. But the real bottleneck is storage.

Battery Tech is seeing exciting innovation. I have worked with a Noida-based Startup working on Sodium-ion batteries using Indian raw materials, bringing down costs by 30% over Lithium. Another one in Pune is experimenting with solid-state storage for EVs, claiming a 500+ km range on a 15-minute charge. These are early-stage bets, but if they crack scale, the export potential is enormous.

The same goes for Green Hydrogen. With the National Green Hydrogen Mission pumping in ₸19,700 crore ($2.3 billion), Startups are experimenting with Electrolysis Tech suited for Indian Climatic and Grid conditions. Some are partnering with Public Sector Units for pilot deployments.

Investors need to understand that these are not SaaS plays. You can’t A/B Test your way to Product-Market

Fit. You need Lab results, certifications, and partnerships with Government or Heavy industry.

Another interesting segment is Space Tech. India saw 140+ Space Startups by the end of 2023. The likes of Skyroot, Agnikul, and Pixxel have validated private sector capability. But now we need to go deeper: propulsion systems, synthetic aperture radars space debris tracking and much more.

One Chennai-based Startup I’m tracking, is building reusable rocket engines using additive manufacturing. They’re not just dreaming big; they’re testing with ISRO. That’s what makes Indian space tech unique access to a strong state ecosystem. The Indian Government asked ISRO to share Tech and its Infra with Private players and that has given wings to the Indian Private Space Startups!

Of course, DeepTech investing in India comes with brutal timelines. No 10x in 12 months here. We’re talking about companies that may take 5 years just to

reach pilot revenues. But I’d rather be early in something hard than late in something easy!

We also need more than Capital. We need Translational Research Centers, better Lab-to-Market programs, IP awareness, and Testbeds. Founders need to know how to pitch to Engineers, Policymakers, Investors and not just VCs.

To Fellow Investors: If your fund has a 5-7-year horizon and you’re looking for predictable growth, DeepTech might not be your game. But if you’re willing to invest in Knowledge, Talent, and Resilience - Welcome aboard.

To Founders: Stay close to the Lab, Work with Academic collaborators, File Patents, Focus on Depth over Speed. And Yes! - Be Stubborn. The market will catch up.

To Policymakers: We need continuity in schemes. DeepTech founders can’t plan around Budget cycles. Drawing from advising over 400 Startups and SMEs across 70+ countries, several key lessons emerge:

1.Localization is Crucial

2.Government-Industry Collaboration is the base

3.Patient Capital is Essential

4.Ecosystem Development is a must

5.Global Benchmarking will get us to compete with China

In conclusion, DeepTech is not a speculative bet. It is a necessity. It’s how India ensures economic resilience, national security, and global relevance. And while exits may take time, the value created will be far greater than just financial returns.

The next decade belongs to founders building for complexity, not convenience. As a Venture Capitalist, I’m placing my bets on them.

Not just for returns but for relevance.

Tushar Kansal Founder & CEO Kansaltancy Ventures

Tushar Kansal is the Founder & CEO of Kansaltancy Ventures – www.Kansaltancy.com, a network of Investors including Venture Capital (VC) Funds, Family Offices, IPO Anchor Investors and Institutional Lenders. He has delivered 500+ Talks/ Shows across Ivy-League academia and Corporates globally, all of which are available in the Public domain - Check TedX/ Google/ YouTube/ Spotify/ LinkedIn. His expert opinion is often sought by leading Channels/ Publications like CNN-News18, VCTV (Venture Capital Tv), Business World & TechThirsty. He contributes to a Portfolio of 400+ Investments in 70+ countries as a Venture Advisor with Loyal VC, a Canadian VC Fund. Awarded multiple times, Tushar is on a mission to assist 25,000 Startups/ SME’s with Funding/ Investments, Management Knowhow and through the network of Kansaltancy Ventures. He is a partner with the biggest Anchor Investor in the SME IPO space, with investments in 115+ IPO’s & AUM of $2.7 Billion.

SkillzzaJob SimulationProgram

India’s DeepTech Revolution: 10 STARTUPS Leading the Charge in 2025

With over 3,600 deeptech startups and a $100 billion R&D push in the latest Union Budget, India’s transformation into a global innovation hub is well underway. Once considered a destination for IT services, the country is now spawning breakthroughs in AI, quantum, and semiconductors.

The Indian government has recognized the sector’s strategic importance. The 2025–26 Union Budget earmarked $100 billion for deeptech R&D, a strong signal that the country intends to be a global leader in future-critical technologies like AI, quantum computing, semiconductors, and advanced materials.

That said, challenges persist. Only around 4% of India’s 100,000+ startups fall under deeptech, compared to 18% in China. Furthermore, only 1 in 6 public-funded incubators cater to deeptech ventures. Yet, partnerships with innovation powerhouses like the U.S., France, Israel, and Germany are helping bridge gaps in funding, infrastructure, and talent.

10 DeepTech Startups to Watch in 2025

Alchemyst AI

Founded in 2023, Alchemyst AI builds autonomous, multi-agent AI employees that integrate into enterprise workflows. Starting with sales development, their platform—Alchemysts—is expanding across functions, enabling digital labor that collaborates, learns, and scales. This agentic AI model is redefining how Indian enterprises boost productivity through intelligent automation.

Deceptive AI

Since 2021, Deceptive AI has focused on AGI (Artificial General Intelligence) through generative and computer vision technologies. Its innovations include fashion GANs, semantic video segmentation, and tools for media production. With roots in fundamental research, Deceptive AI is pioneering AI for India’s creative economy.

Intrvuz

Ivelosi

A 2025 entrant, Ivelosi is disrupting connectivity itself. It’s building a decentralized, AI-powered communication protocol that eliminates the need for ISPs. Using unlicensed WiFi spectrum and blockchain-authenticated peer-to-peer networking, Ivelosi offers affordable and resilient digital infrastructure—a game-changer for rural and underserved regions.

Intrvuz is reshaping hiring through autonomous recruitment intelligence. Its platform automates screening, interviewing, and matching talent to roles, reducing time-to-hire by up to 90%. For a country managing large-scale employment demands, Intrvuz brings scalability and precision to workforce acquisition.

RoomsVital Automation Solutions

Focused on IoT and automation, RoomsVital retrofits homes and hospitality spaces with intelligent locks, sensors, and visitor management systems. By enabling self-check-ins and enhanced security, it’s accelerating India’s smart infrastructure—without requiring new construction or complex installs.

Autoyos Private Limited

Autoyos is designing operator-free AI systems for healthcare, including diagnostic and monitoring devices that function autonomously. Their mission: make quality healthcare accessible in Tier 2 and Tier 3 cities by removing dependency on human operators. Their work could radically improve India’s medical reach and reliability.

08

Alt DRX

Alt DRX is transforming real estate with fractional ownership. Its blockchain-powered marketplace allows users to buy and sell tokenized property—one square foot at a time—with real-time pricing and liquidity. By democratizing real estate investment, Alt DRX is unlocking a $200+ billion sector for the masses.

09

Uniphore

Already a global name in conversational AI, Uniphore analyzes speech, emotion, and intent to power human-centric digital experiences. With applications in CX, healthcare, and compliance, Uniphore ensures machines not only understand language—but understand people.

DocketRun

In the retail world, DocketRun helps brands decode consumer behavior using video analytics. Their platform provides actionable insights from in-store and digital interactions, helping companies optimize marketing, inventory, and customer service. It’s retail intelligence in real time.

10

Qure.ai

Qure.ai applies deep learning to radiology, enabling rapid diagnostics for tuberculosis, stroke, and brain injuries. Its tools are in use across more than 60 countries, with a strong impact in rural India where access to skilled radiologists is limited. Qure.ai is a frontrunner in India’s AI-for-healthcare mission.

What’s Powering the Rise?

India’s deeptech boom is fueled by four key enablers:

•Government Policy: The historic $100B R&D budget shows long-term commitment.

•Global Collaboration: Strategic ties with the U.S., EU, Israel, and Japan are opening research and funding pipelines.

•Academic-Industry Synergy: Institutions like IISc, IITs, and private accelerators are incubating high-caliber talent.

•Private Capital: VC interest in frontier tech is growing, especially in climate, space, biotech, and AI.

The Road Ahead

India’s deeptech startups are not just building companies, they’re tackling civilization-scale problems: climate resilience, AI alignment, decentralized infrastructure, and next-gen healthcare. The momentum is here, but to sustain it, India must:

•Increase funding access beyond Tier 1 cities

•Build more deeptech-focused incubators and labs

•Incentivize commercialization of research outputs

•Nurture academia-industry-government partnerships

2025 is a watershed moment in India’s innovation journey. With strategic investments, global collaborations, and a bold new generation of technologists, India is not just building for today. It’s architecting the future.

REIMAGINING PREVENTIVE HEALTHCARE:

AI AND REAL-TIME VITALS

TRANSFORM HEART DISEASE DETECTION

Heart disease remains one of the significant causes of death worldwide (especially in India). Despite advancements in treatment, many people don’t discover they have heart issues until it’s too late. A reactive approach to healthcare only intervenes once symptoms have emerged, which is no longer sufficient.

What if we could catch heart problems before they even appear? Imagine technology that works 24/7 to detect the early signs of cardiovascular disease (CVD), allowing us to take preventive action before it’s too late.

Thanks to the latest advancements in real-time vital monitoring, wearable tech, and artificial intelligence (AI), we’re on the verge of a revolution in heart health. The future of health care is here, and it’s all about proactive prevention, not reactive treatment.

The Problem with Traditional Heart Disease Detection

Traditional healthcare models have been built around treating problems as they arise. Regular checkups, screenings, and doctor visits are essential, but they only offer a snapshot of health at a specific point in time. Between those visits, several health changes can go unnoticed.

Heart disease often develops slowly. Small shifts in heart rate, blood pressure, or sleep patterns can be the first signs of a problem, but they usually go undetected until they become more noticeable.

This leaves a significant gap in the system: a period when heart disease may be silently progressing without anyone noticing. How can we address this issue?

Utilising technology, such as wearable devices, can help us continuously monitor our health.

Real-Time Monitoring of Crucial Data

Real-time vital monitoring does the magic. AI-powered wearables can track key health indicators, such as heart rate, blood oxygen levels, stress, and sleep patterns, all day, every day. This kind of constant

monitoring provides us with a comprehensive overview of our health, enabling us to detect early signs of heart disease before they become apparent in a doctor’s office.

Having access to continuous data means we no longer have to wait for symptoms to appear; instead, we can take action immediately. Instead, we can identify patterns and trends in our health in real time, allowing us to take preventive steps early on.

Wearables: From Step Counters to Health Guardians

Wearable devices have come a long way since their introduction to the market. Initially, they were just step counters or fitness trackers. Now, modern wearables are sophisticated health tools that can measure:

•Heart rate variability (HRV)

• Blood oxygen levels (SpO₂)

•Sleep quality

•ECG (electrocardiogram) signals

•Stress and recovery patterns

These devices provide a non-invasive and easy-to-use method for collecting valuable health data. They are also designed to integrate seamlessly into daily life, providing constant feedback without disrupting daily routines.

Wearables are transforming from simple fitness gadgets into powerful health monitors, making it easier than ever for individuals to track their heart health on their terms. With real-time insights, users can make informed decisions about their health and take action before minor issues escalate into major ones.

AI: Turning Data into Actionable Insights

While wearables collect data, AI makes sense of it. AI-powered systems can analyse massive amounts of data in real-time, looking for patterns that would be impossible for humans to spot on their own.

For example, AI can detect subtle changes in heart rate

A personalised approach to healthcare means that interventions are far more accurate and relevant to the individual. It’s not about treating everyone the same; it’s about understanding what’s “normal” for you and providing recommendations based on your health data. or sleep patterns that suggest early signs of cardiovascular strain. It can also predict future risks of CVD based on an individual’s health history and real-time data, providing tailored recommendations on how to prevent heart disease before it even starts.

This represents a significant leap forward in our approach to heart health. Instead of relying on generic advice, AI helps provide personalised insights that are specific to each individual’s unique health profile.

Personalised Healthcare: One Size Does Not Fit All

One of the key benefits of AI and real-time monitoring is personalisation. Traditional healthcare often uses one-size-fits-all guidelines — for example, the same ideal heart rate range for everyone. But that doesn’t work because each person’s body is different.

AI solves this problem by learning an individual’s unique health patterns. For example, your normal heart rate may differ from someone else’s, and your recovery after exercise may also be unique to you. AI can track these personal baselines over time, spotting subtle changes that might indicate a problem.

Why Preventive Healthcare Matters?

Preventive healthcare isn’t just a buzzword; it’s a necessity for an Indian heart. CVD and other heart diseases are causing death, and the earlier we detect them, the more effectively we can manage them.

Catching heart disease early can reduce the need for costly, invasive treatments. Many heart issues can be managed with simple lifestyle changes or medication when they’re detected early enough.

The shift to preventive healthcare also benefits society as a whole. When people stay healthier for longer, healthcare costs decrease, quality of life improves, and the burden on healthcare systems is alleviated. For businesses like Helius Wellness, promoting heart health through wearable devices and AI-driven insights fosters

Solving Challenges with a Preventive Care Approach

As the future of preventive healthcare appears promising, attention is being given to the challenges that have been observed. Health data is being handled with utmost care, with companies offering these technologies prioritising robust data protection and security measures to ensure patient privacy is safeguarded.

AI models are continuously improving, trained with diverse and representative data to enhance their accuracy. These systems are not only making reliable

Paresh Masani Founder & CEO

Helius Wellness

Paresh Masani is a visionary technology leader and founder, reshaping the future of digital health through AI-driven innovation. As the Founder & CEO of Helius Wellness, he is building India’s first AI-powered preventive heart health platform – leveraging proprietary wearables, real-time vitals, and neural networks to deliver early detection and personalised care at scale.

A Gold Medalist in M.Tech (CSE), honoured by the late Dr. A.P.J. Abdul Kalam, Paresh has deep expertise in engineering leadership, system architecture, and AI integration. With a track record of building $1B healthtech platforms and scaling global engineering teams, he is on a bold mission to prevent premature heart disease deaths in India, driving the convergence of technology and wellness to reimagine healthcare for emerging and developed markets.

Beyond Automation: Agentic AI and the Future of Independent Intelligence

A New Kind of Intelligence Is Emerging

Imagine a digital analyst who doesn’t just wait for your instructions—but proactively monitors global markets, analyzes trends, makes decisions, and learns from outcomes. It doesn’t sleep. It doesn’t wait. It acts.This is not the future. This is Agentic AI—the next leap in ar tificial intelligence.But to understand where we’re going, we must first understand how we got here.

The Evolution of AI: From Rules to Reasoning

The journey of AI has been one of increasing sophistication and autonomy:

• Rule-Based Systems (1950s–1980s): Early AI followed strict logic. It could play chess or solve equations—but only within rigid boundaries.z- Machine Learning (1980s–2010s): AI began learning from data, enabling predictive models in finance, healthcare, and marketing.

• Deep Learning (2010s–2020s): Neural networks unlocked breakthroughs in image recognition, speech, and natural language.

• Generative AI (2020s): Models like GPT-4 and DALL·E could now generate human-like text, images, and code.

• Agentic AI (Emerging): AI that doesn’t just respond—it perceives, decides, acts, and learns.

Generative AI: The Creative Catalyst

Generative AI has transformed industries. Powered by Foundation Models and Large Language Models (LLMs), it can write emails, generate reports, draft legal documents, and even design products.

But its real power lies in contextual intelligence—especially when paired with RAG (Retrieval-Augmented Generation) architecture.

What is generative AI?

•Creates new content and ideas, including conversations, stories, images, videos, and music

•Powered by large models that are pretrained on vast corpora of data and commonly referred to as foundation models (FMs)

Evolution of AI

RAG Architecture

How LLMs retrieve relevant data and generate grounded responses.

Agentic AI: Intelligence That Acts

While Generative AI is impressive, it still waits for a prompt. Agentic AI goes further. It’s proactive. It’s autonomous. It’s goal-driven.

An Agentic AI system can:

• Perceive its environment

•Decide what to do

•Act on those decisions

•Learn from the results Example:

A supply chain agent monitors weather, inventory, and traffic. It reroutes shipments, updates customers, and negotiates with vendors—without human input. This is not just automation. This is autonomous intelligence.

What is Agentic AI?

Agentic AI is a type of artificial intelligence that can make decisions and take actions on its own.

Agentic AI andle Complex and Unpredictable situation.

•Adapt and learn Over Time.

•Make Autonomous Decisions.

The Agent Loop: How It Works

At the heart of Agentic AI is a continuous feedback cycle known as the Agent Loop: Infographic: The Agent Loop

Perception Decision-Making Action Learning 1. Perception: Gathers data from APIs, sensors, or documents.

2. Decision-Making: Evaluates options based on goals and context.

3. Action: Executes tasks—sending emails, placing orders, updating systems.

4. Learning: Adapts based on feedback and outcomes. This loop allows agents to evolve over time, becoming smarter and more effective.

Traditional AI vs. Agentic AI: A Strategic Comparison

Traditional AI vs. Agentic AI: A Strategic Comparison

FeatureTraditional AIGenerative AIAgentic AI

AutonomyLow Medium High

LearningStatic

Iterative Continuous

Decision MakingProgrammedPromptedAutonomous

ScalabilityLimited Good Excellent

IntegrationPoint SolutionAPI-BasedFull System

Agentic AI doesn’t just optimize processes—it redefines them.

Types of Intelligent Agents: The Building Blocks

Understanding the types of agents helps in designing the right solutions:

- Simple Reflex Agents: React to current inputs (e.g., thermostats).

- Model-Based Reflex Agents: Use internal state for better decisions.

- Goal-Based Agents: Choose actions that achieve specific objectives.

- Utility-Based Agents: Optimize for the best possible outcome.

- Learning Agents: Continuously improve through feedback and experience.

These categories form the foundation of Agentic AI design.

Real-World Applications: Where Agentic AI Is Already Working

Agentic AI is already transforming industries:

- Autonomous Vehicles: Navigate traffic, avoid collisions, and optimize routes.

- Healthcare: Virtual agents assist in diagnostics, monitor patients, and suggest treatments.

- Finance: AI traders analyze markets, execute trades, and manage portfolios.

- Smar t Homes: Agents manage lighting, security, and energy consumption.

- Customer Service: AI agents resolve queries, escalate issues, and learn from interactions.

- Agriculture: Drones and bots monitor crops, apply fertilizers, and predict yields.These are not pilots—they’re production systems delivering ROI.

Generative + Agentic: Better Together

Think of Generative AI as the brain and Agentic AI as the body.Generative AI provides creativity, language fluency, and reasoning. Agentic AI adds autonomy, decision-making, and execution.Together, they enable end-to-end intelligent systems—from understanding a problem to solving it autonomously.

Frameworks Powering the Agentic Revolution

Several frameworks are enabling developers to build Agentic AI systems:

- CrewAI: Enables multi-agent collaboration with defined roles and memory sharing.

- AutoGen (Microsoft): Facilitates LLM-based agents that collaborate and solve complex tasks.

- LangGraph: A graph-based orchestration framework for building agent workflows. These frameworks abstract the complexity of agent design, making it easier to deploy intelligent systems at scale.

Deep Dive: CrewAI in Action

Among these, CrewAI stands out for its modularity and enterprise readiness. It allows developers to:

• Define agents with specific roles (e.g., researcher, planner, executor)

• Enable collaboration between agents (crews)

• Share memory and context across tasks

• Execute workflows in parallel or sequence

This makes CrewAI ideal for complex, multi-step business processes—such as market research, compliance audits, or product development.

Use Case: Stock Analyst Agent

Let’s bring it all together with a real-world example. The Stock Analyst Agent, built using CrewAI, operates as follows:

• Perception: Monitors financial news, stock prices, and economic indicators.

• Decision-Making: Analyzes trends, evaluates risk, and identifies investment opportunities.

• Action: Recommends or executes trades based on predefined strategies.

• Learning: Refines its models based on market feedback and performance metrics. This agent doesn’t just assist a human analyst—it becomes one. And it operates 24/7, without fatigue, bias, or delay.

Executive Insights: Why This Matters Now

For C-suite leaders, Agentic AI is not just a technological trend—it’s a strategic imperative.

• Scalability: Agents can operate across geographies and time zones

• Resilience: They adapt to change in real time

• Efficiency: They reduce costs and free up human talent

• Innovation: They unlock new business models and revenue streams

Mini Case Studies: Industry Snapshots

• Healthcare: A hospital uses agents to manage patient flow, reducing ER wait times by 30%.

• Finance: A hedge fund deploys AI traders, increasing returns while reducing risk.

• Agriculture: A cooperative uses drones and bots to boost yield and cut pesticide use.

Implementation Strategy: How to Get Started

• Start Small: Pilot with a focused use case.

• Build Cross-Functional Teams: Blend tech, ops, and domain experts.

• Choose the Right Framework: CrewAI, AutoGen, LangGraph.

• Invest in Training: Upskill your teams to manage and evolve AI systems.

• Govern Wisely: Establish ethical and operational guardrails.

Vision for the Future: Autonomous Enterprises

We’re just scratching the surface.

In the next 3–5 years, expect to see:

•AI marketplaces where agents buy, sell, and negotiate.

•Human and Agent collaboration as the new normal.

Conclusion: The Future Is Agentic

The age of passive AI is ending. The age of Agentic AI has begun.

For CIOs, CTOs, and business leaders, the question is no longer if—but how fast you can adapt.

Because in the near future, your most valuable team member might not be human—it might be an agent.

Rahul Rai Head Service Management Platform Syngenta

Rahuul Raaii is a visionary global leader driving enterprise transformation through technological excellence and strategic innovation. With deep expertise across SAP technologies, Business Intelligence, Service Management Platforms, he has held pivotal roles as Product Owner, Application Lead, and Service Delivery Manager. Rahuul has successfully implemented Business Intelligence, Generative AI, Reporting Factory, Agile, Scrum, and DevOps methodologies fostering operational agility and continuous improvement.

A pioneer in automation and digital analytics, Generative AI capabilities, leveraged AI, ML, predictive modeling and sentiment analysis to enable data-driven decision-making. At the forefront of innovation, he is actively exploring use cases for Agentic AI, Generative AI, Microsoft Copilot, and SAP Joule across enterprise systems. A collaborative leader, Rahuul excels in stakeholder engagement, vendor partnerships, change management, and mentoring future tech leaders.

HOW

ARE WINNING WITH STRATEGIC FUNDRAISING

DeepTech is finally making a splash in India. Driven by entrepreneurs who are frequently more at ease in labs than in boardrooms, the movement has taken years to gain traction. As someone who has advised many startups across countries, I’ve had a ringside view of how DeepTech ventures, often misunderstood, underfunded, and deeply complex, are now emerging as serious contenders for both capital and impact.

India’s DeepTech evolution didn’t follow the pattern seen in Silicon Valley. There, DeepTech often grew out of academia and government defense projects. Here, it is more heterogeneous. Some startups are spinning out of research labs like IISc and IITs, while others are emerging from niche B2B needs in healthcare, automation, and cybersecurity. What binds them is a deep-rooted technological moat, be it AI, robotics, space-tech, or quantum computing, and a hunger to solve core infrastructural or scientific challenges.

Unlike app-based consumer startups, which scaled rapidly with marketing blitzes and shallow tech, DeepTech ventures are forging their paths in quiet, methodical ways. Their roadmaps are longer, their capital requirements higher, and their exits often less glamorous but their impact is exponential.

Strategic fundraising becomes not just necessary, but existential for these companies. DeepTech startups

require patient capital, often needing 7-10 years before hitting breakeven or commercialization. This changes the nature of the pitch itself. While a SaaS founder might talk ARR and CAC, a DeepTech founder talks TRL levels (Technology Readiness Levels), IP development timelines, and regulatory pathways. Convincing investors demands a different language.

Over the years, I've seen this play out repeatedly. A robotics startup I advised was struggling to raise funds through traditional VC channels because their revenue projections looked modest on Excel. But when reframed as an automation solution to a global supply chain crisis validated by large industrial clients, the same model became investable. It’s not always about tweaking the story; sometimes it’s about knowing which lens investors are looking through.

In 2024, nearly two-thirds of Indian DeepTech startups are in AI/ML and data science. This segment alone attracted 87% of total DeepTech funding in the first half of the year. And yet, DeepTech is much broader than just generative AI. Take aerospace: ISRO’s reforms and the establishment of IN-SPACe have opened up new commercial possibilities. Satellite communication, earth observation, and even launch vehicle startups are raising capital like never before. Pixxel, GalaxEye, and Skyroot have all made global headlines and attracted global investors.

Vandana Tolani Founder & CEO, Convanto

Healthcare and biotech are another frontier. Companies like Niramai and Tricog are showing how AI can work in diagnostics. India’s massive population makes it an ideal test bed for scalable healthcare tech, especially when AI is paired with low-cost hardware or IoT solutions. Add to this the new bio-manufacturing policy, and we have fertile ground for innovation in biosciences. India’s biotech industry is already valued at over $80 billion and is expected to reach $150 billion by 2025. With over 5,000 biotech startups today, the pace of growth is unmatched.

Cybersecurity and quantum tech, though still in early stages, are gaining traction thanks to national policy. The National Quantum Mission, with an outlay of ₹6,000 crore, aims to position India among the top three nations in quantum technologies. Startups like QNu Labs and QpiAI are experimenting with quantum key distribution and secure enterprise frameworks. This sector will not mature overnight, but we’re planting the seeds now. India aims to develop quantum computers with 1,000 qubits by 2031, an audacious goal, but one that signals strategic intent.

I want to dwell for a moment on robotics and automation. While the term conjures up factory bots or humanoids, India’s approach is more functional. GreyOrange is optimizing warehouse logistics. Genrobotics has built sewer-cleaning robots to eliminate manual scavenging. These aren't sexy in the typical startup sense, but they are transformative. In 2023, industrial robotics adoption in India grew by 24%, driven by manufacturing and logistics firms seeking efficiency. The push from the government’s Smart Cities initiative also plays a role here.

Even defense and space are seeing private participation. We now have ISRO collaborating with startups and a ₹1,000 crore VC fund for space tech on the anvil. The government's Production-Linked Incentive (PLI) schemes, combined with Make in India momentum, are encouraging homegrown hardware ventures in drones, semiconductor design, and energy storage. The Ministry of Defence cleared over 150 startups under the Innovations for Defence Excellence

(iDEX) program by mid-2024, showing the state’s growing openness to startup solutions in critical sectors.

Let’s talk about the types of capital that are flowing into DeepTech. Traditional VCs still find it difficult to back these ventures unless they see product-market fit or scalable revenue. The average Indian VC fund has a 7-10 year lifecycle. That doesn’t align well with a DeepTech startup that may need 4-5 years of R&D before commercialization. Which is why we’re seeing a rise in sector-specific funds, family offices, and strategic corporate investors entering the fray. Companies like Reliance, Tata, and Adani are either incubating or investing in DeepTech capabilities.

Additionally, alternative capital models are gaining traction. DeepTech-focused venture debt, government-backed seed programs, and corporate venture capital arms are all providing pathways to non-dilutive or patient capital. Public institutions like SIDBI, DST, and BIRAC are playing catalytic roles. In 2023 alone, BIRAC disbursed over ₹1,200 crore in funding support across biotech and MedTech innovations.

Furthermore, global investors, particularly from Europe, Japan, and the US, are sniffing around for emerging market innovation. Unlike China, where DeepTech is often state-sponsored, or the US where it’s VC-heavy,

Public-private collaboration is our best bet. IIT-Madras’s collaboration with DRDO, or BIRAC’s grants for biotech innovators, are good examples. But we need more structured innovation pipelines.

Israel offers a compelling case study. Over 50% of Israeli DeepTech startups originate in university labs, and the government provides substantial early-stage support through the Israel Innovation Authority. The country spends 4.9% of its GDP on R&D, compared to India’s 0.7%. The contrast is stark. In the US, the National Science Foundation and DARPA act as high-risk early funders, ensuring DeepTech projects don't wither on the vine. Europe, on the other hand, combines research institutions with long-term grants like Horizon Europe, which allocated over €95 billion to research and innovation through 2027.

India’s comparative advantages lie elsewhere. Our engineering talent pool is vast. Our costs are lower. Our problems, whether healthcare access, energy storage, or crop productivity, are large enough to demand DeepTech solutions. But we need to improve our IP frameworks, cross-border R&D collaboration, and university incubation models. In India, less than 5% of patents come from universities. This bottleneck must be addressed if we want to create a reliable pipeline of DeepTech innovation.

Regulation matters too. The draft Digital India Act, semiconductor policies, data protection laws all impact DeepTech’s future. Entrepreneurs often underestimate the time it takes to align with regulatory standards, especially in sectors like health and defense. Investors, meanwhile, worry about lack of exit options. Unlike SaaS, where M&A is frequent, DeepTech exits are fewer and often strategic. In India, the M&A market for DeepTech remains nascent, with fewer than 10 such transactions recorded in 2023, compared to over 200 in the US.

From advising hundreds of startups, one clear lesson emerges: storytelling in DeepTech must evolve. It’s not just about what your technology does, it’s about why it matters now, how it changes industry cost structures, and how it scales across markets. Founders must speak to both engineers and financiers, sometimes in the same breath. This is harder than it looks. But those who master it win.

I'll give you a recent example. High-fidelity simulators were being built by a quantum computing startup I worked with. At first, they concentrated their outreach on hardware specifications and scholarly citations. We assisted them in shifting their focus toward better protein folding, quicker drug discovery, and use-cases in pharmaceutical simulations. Enterprise Pharma was suddenly paying attention. They are currently negotiating with strategic investors and international labs.

Strategic fundraising, especially in DeepTech, is not about chasing the biggest valuation. It’s about finding capital aligned with your vision and risk horizon. In India, this often means hybrid models: initial grants from BIRAC, followed by strategic angels, then a mix of VC and CSR-backed incubators. It's slow, yes but it builds resilience.

The future of DeepTech in India hinges on a few pillars. One, deeper university-industry collaboration. Two, patient and smart capital that understands tech timelines. Three, policy frameworks that reduce friction without stifling innovation. Four, more domestic

talent. India produces nearly 1.5 million engineers annually, but only a fraction specialize in frontier tech. Investments in postgraduate and postdoctoral research must rise.

We’re already seeing signs of this shift. Zepto’s recent success shows that even in quick commerce, operational innovation matters. But DeepTech is playing a longer game. Its payoff isn’t in viral downloads or GMV spikes, but in tectonic shifts in how we diagnose diseases, build satellites, secure data, or store energy.

India was late to the 4G party and missed the semiconductor revolution. But there is an opportunity to lead with DeepTech. We are not required to follow Shenzhen or the Valley. Our scientific talent, scaled through economical innovation, and fueled by capital that prioritizes depth over speed allow us to forge our own path.

India’s DeepTech startup ecosystem has the ingredients for global leadership scientific talent, market depth, rising capital availability, and geopolitical alignment with technology democracies. India's DeepTech startup ecosystem has world-class scientific talent, a deep market, increasing capital availability, and geopolitical alignment with technology democracies. However, systemic investments, long-term planning,

Vandana Tolani

Founder & CEO Convanto

Vandana Tolani is the Founder and CEO of Convanto, a leading boutique investment bank in India, now in its 12th year. With over 20 years of global experience, she was previously the Managing Director for a family office fund. For the past 12 years, she has been leading Convanto, where she has supported 357 companies across 45 countries and five VC funds with fundraising and strategic advisory. Her achievements include being named Woman Entrepreneur of the Year (2021–2023), Top 10 Women Leaders in Wealth Management, and Global Woman Leader by the World Women Congress. She has been featured in leading publications such as the Times of India and Hindustan Times, and honored by Dr. Kiran Bedi and Hema Malini for her contributions to the startup ecosystem. On Women Entrepreneurs Day 2024, she was recognized among the Top 8 Women Entrepreneurs, and on March 8, 2025, among the Inspiring Women Leaders. She has delivered 350+ talks, listed on www.convanto.com

and institutional patience are necessary to realize full potential.

In order to gain momentum, India needs to:

1.Establish translational research centers in both Tier I and Tier II universities.

2.Connect startup ecosystems with procurement for space, defense, and climate technologies.

3.Provide Series B through D ventures with growth-stage DeepTech funding.

4.Promote international research collaborations, R&D tax credits, and IP buyouts.

I remain optimistic. The next decade will be India’s DeepTech decade if we get the funding, storytelling, and policy mix right. And if we do, it won’t just change our startup landscape. It will change our economy, our society, and our place in the world.

REVOLUTIONIZING RADIOLOGY: HOW DEEPTECH AND GENERATIVE AI ARE SLASHING SCAN TIMES AND TRANSFORMING GLOBAL HEALTHCARE

MRI is a golden standard for diagnosis of Cancer, Neurodegenerative disorder, Stroke and other ailments. However, MRI is a slow, costly and inconvenient process for patients. MRI takes 30 mins - 1 hr for a scan and patients feel claustrophobic inside the machine. There is also a long waiting time up to 1 year in public hospitals for MR scanning appointments. So there is a huge need to reduce MR scanning time and waiting time. Aikenist has developed a unique technology that helps to reduce MRI scanning time as well as to improve quality of the MRI scan.

MRI technology uses Magnets and Coils which excites hydrogen atom’s protons and uses time constant to stabilize the spin to plot different tissues of the body. Since hydrogen atoms are present in all tissues in different quantities, the tissue characteristics vary which is useful in good delineation of anatomy and tissue properties within the human body. This helps to detect and characterize tumours, spinal disorders, stroke characteristics. The findings based on MR scanning help in proper detection of disease and treatment to patients.

MRI scanners are based on Magnetic strengths. Popular MRI scanners are 1.5T and 3T MRI scanners. The magnets and coils of MRI scanners are part of hardware in all these machines. Hardware technology has been constant for a long time. What changes in MRI scanning technology is the post processing software to improve the scan quality specifically to improve the Signal to Noise Ratio (SNR). In order to improve SNR, the popular algorithms used in most machines available today are based on image processing. However these algorithms provide suboptimal results and require more samples to increase the SNR. This is highly inefficient as it takes more time to scan the patient.

The solution is to use the AI based algorithms which can provide better SNR with less number of samples acquired.

The latest scanners come with AI based post processing technology embedded in the machine. However this approach is not very suitable in the long term as post processing technology keeps changing every 2 years and newer algorithms provide better results compared to the previous algorithms. The best

suited approach for upgradability is to provide the software based solutions which work external to the machine and compatible with all the existing machines.

Aikenist has developed patented AI based algorithms to improve the SNR post acquisition of the scans. The scan time can be reduced by acquiring scans with the fast protocol and post processing the acquired scans to improve the SNR. Aikenist has used Generative AI based method which is the most advanced technology. This has resulted in reducing time by up to 50%, this means a 30 min scan can be done in 15 mins. This 30 mins is the time spent by the patient inside the magnetic bore. This improves patient convenience and helps in increasing the number of scans per machine so that more patients can be addressed with the same infrastructure.

This is very important for public healthcare since there is huge demand to provide advanced care to the population. This also helps to improve the affordability of such diagnostic services.

The solution is validated in clinical trials where Radiologists have agreed that the solution provided good delineation of anatomy and pathology. The solution is regulatory approved by CDSCO.

This kind of technology has the potential to reduce the MR scanning time to less than 5 mins. This means the patient walks in and out for a scan in 5 m paying 70% less than today.

5m Screening for risks for Cancer, Body, Health, Stroke, Chest & Heart in next 5 years.

Ashwin Amarapuram

Director & CEO

Aikenist

Ashwin is Director & CEO of Aikenist. Ashwin has decades of experience in building AI product companies. Ashwin holds several patents and publications, and has a master's degree from IISc.

Aikenist is a Bangalore-based MedTech company specializing in advanced AI solutions for all aspects of radiology, including PACS and RIS. Aikenist solutions are FDA certified and installed in more than 500 locations in India and abroad.

Ecosystem-Led Growth: How Strategic Alliances are

Driving AI And Cloud Adoption

Organizations today face mounting pressure to reinvent their operations, customer experiences and business models through AI and cloud technologies. Yet many struggle to move beyond pilot projects or isolated use cases. The answer lies not in going it alone, but in orchestrating a vibrant ecosystem—one that brings together hyperscalers, independent software vendors (ISVs), global system integrators (GSIs) and innovative startups to co-create solutions, accelerate time to value and share in success.

Innovation Velocity

Rapid pace of new developments

Why Ecosystems Matter

Depth & Scale

Extensive reach and comprehensive capabilities

Integration Expertise

Seamless connect different components and systems

No single vendor can deliver the full stack of capabilities required for modern digital transformation. AI demands data readiness, model expertise, governance frameworks and scalable infrastructure. Cloud transformation encompasses migration services, security, cost optimization and ongoing modernization. Ecosystems unlock complementary strengths:

•Depth and Scale: Hyperscalers provide the foundational platforms, unmatched scale and global reach that few organizations can replicate.

•Specialized IP: ISVs contribute pre-built applications and accelerators that embed industry best practices and jump-start deployment.

•Integration Expertise: GSIs and consultancies bring deep change-management skills, process transformation know-how and the human network to shepherd large-scale implementations.

Specialized IP

Unique intellectual property and Knowledge

Fueling AI Adoption through Alliances

Building AI into core operations is seldom a straight line. Early servers-and-scripts experiments can stall when companies hit complexity walls around data quality, security reviews and ethical guardrails. Strategic alliances help companies navigate these hurdles by:

•Innovation Velocity: Startups inject fresh thinking, niche AI algorithms and agile delivery models, enabling rapid experimentation and differentiation.

Together, these partners form a flywheel: successful joint projects lead to new referenceable use cases, which drive broader adoption and unlock additional co-investment.

•Pooling Data and Models: Partnerships between industry leaders and cloud providers can result in secure data-sharing enclaves, enabling federated learning across organizations while preserving privacy.

• Embedding AI into Workflows: ISVs increasingly offer pre-trained models for vertical processes—credit underwriting, predictive maintenance, customer churn scoring—that plug directly into existing systems. By co-marketing these solutions with hyperscalers, they drive adoption among enterprises intimidated by building models from scratch.

•Scaling Responsibly: Joint R&D labs and innovation centers—often funded by hyperscalers and led by GSIs—provide governance frameworks, bias-testing protocols and compliance checklists. This collaboration accelerates production time while attenuating risk.

Accelerating Cloud Adoption through Joint GTM

Cloud transformations also benefit from the ecosystem approach. Instead of one-off lift-and-shift projects, alliances create packaged offerings that blend migration services, security controls and managed-services commitments under a single commercial umbrella. Key levers include:

•Co-funded Migration Programs: Hyperscalers often offer migration credits or rebates when partners deliver a defined volume of migrations, lowering net cost and aligning incentives.

• Industry-Specific Blueprints: Collaborations with ISVs and GSIs yield reference architectures tailored to sectors such as financial services, manufacturing or healthcare—accelerating adoption and reducing architectural uncertainty.

Case in point: A leading retail chain partnered with its cloud provider and a specialist AI startup to deploy a real-time demand-forecasting engine. The startup contributed to a deep-learning model for promotional uplift; the cloud partner provided elastic GPU clusters and MLOps pipelines; and a global system integrator managed integration with merchandising systems and user training. The result: a 15% improvement in stock-out avoidance within three months and a blueprint for global roll-out.

Five Success Factors for Ecosystem-Led Growth

Joint Demand-Generation Campaigns: Marketing Development Funds (MDF) enable partners to co-invest in shared-account outreach, webinars and thought leadership, driving pipeline more efficiently than solo efforts.

A recent example: A global pharmaceutical company leveraged a blueprint co-developed by its cloud provider, a GSI and a data-analytics ISV to migrate its R&D platform. The cloud partner underwrote half the migration cost, the GSI provided transition-management expertise, and the ISV integrated data-governance modules. Within six months, the company achieved 40% cost savings on data storage and unlocked new analytics use cases for drug discovery.

•Joint Vision & Incentives: Align on measurable KPIs—pipeline, deal velocity, customer-satisfaction—and embed them in partner scorecards.

•Formalized Governance: Establish an alliance management office to drive business reviews, co-innovation workshops and escalation paths.

•Shared IP & GTM Assets: Develop reference architectures, demo environments and marketing collateral that showcase the joint solution.

•Seamless Customer Experience: Harmonize commercial terms, support models and successful metrics so clients see one unified team.

•Continuous Enablement: Maintain joint training programs, certification tracks and a partner portal for best practices, solution updates and market insights

Real-World Illustration

•Financial Services Co-Innovation: A major bank, its cloud hyperscaler and a cybersecurity ISV built a real-time streaming fraud detection platform, reducing false positives by 30% while preserving compliance.

• Manufacturing Digital Twin: An industrial OEM, working with a GSI and a startup AI firm, created digital-twin models that predicted equipment failures 48 hours in advance, cutting unscheduled downtime costs by 25%.

•Healthcare Interoperability Hub: A hospital network, collaborating with an

integration-platform ISV and a cloud AI team, launched a patient-data exchange that uses NLP to standardize records—accelerating care coordination and halving manual documentation.

Actionable Strategies for Leaders

•Map Your Ecosystem: Conduct a partner-landscape assessment to identify gaps and co-innovation opportunities.

•Pilot Smart, Scale Fast: Start with a marquee use case, prove the model, then replicate across lines of business and regions.

•Invest in Relationship Capital: Beyond contracts, nurture personal connections through off-sites, executive councils and hackathons.

•Measure, Learn & Iterate: Use integrated dashboards on pipeline, implementation velocity and customer feedback; hold regular retrospectives to refine joint processes.

AI and cloud adoption no longer live in separate silos; they converge in ecosystems that unite the best of platforms, specialized applications and integration prowess. Strategic alliances are the rocket fuel for digital transformation—de-risking innovation, scaling rapidly and delivering measurable business impact. By embracing an ecosystem-led growth mindset—grounded in shared vision, co-developed IP and seamless customer experience—senior business leaders can turn partnerships into powerful engines of AI-driven, cloud-powered competitive advantage.

SURAJ ATREYA

Strategic Partner Alliances

Marketing Leader

Rackspace Technology

Suraj Atreya is a Strategic Partnerships and Global Marketing Leader with over 15 years of international experience driving enterprise growth and market presence through ecosystem driven go to market strategies across AI, Data, Cloud, and emerging technologies. He is known for aligning marketing with business priorities, expanding partner ecosystems, and turning strategic alliances into sustained demand and revenue opportunities.

An executive alumnus of IIM Calcutta, Suraj is a recognized thought leader featured in global forums for shaping next generation go to market practices. He also serves as Chapter Host for Partnership Leaders in Bangalore (India), bringing together senior executives to define the future of ecosystem growth. Respected for his ability to position companies for success in competitive markets, Suraj builds strategic marketing and partner alliance programs that strengthen perception, accelerate pipeline, and deliver long-term enterprise value. He also mentors startups and advises early-stage ventures focused on scaling through ecosystem partnerships.

REWIRING INNOVATION: A DEEP DIVE WITH SUBHAJIT SARKAR ON GEN AI, DEEPTECH, AND HUMAN-CENTRIC TRANSFORMATION

In the rapidly shifting industrial landscape, few voices offer both strategic depth and practical clarity like Subhajit Sarkar. With over two decades of experience guiding Fortune 500s and mentoring startups, he brings a rare lens to the convergence of DeepTech and business transformation.

In this candid conversation, he shares his journey, insights, and the emerging playbook for leaders navigating the future of intelligent industry.

You’ve spent over two decades at the intersection of technology and business strategy, working with global giants and emerging innovators alike. What first drew you into the world of Deep Tech and Industry 5.0, and how has your journey evolved since then?

It wasn’t just the allure of cutting-edge tech for me, it was the impact potential. Early on, I realised true innovation lies at the intersection of science, business value, and human need.

Deep Tech challenges us to rethink what’s possible—whether it’s AI redefining diagnostics, quantum shaping energy, or advanced robotics transforming supply chains.

Subhajit Sarkar is an accomplished CXO, startup mentor, and DeepTech advisor with 21+ years of experience at the intersection of technology and business transformation. Leveraging advanced technologies like Gen AI, AI/ML, IoT, and Blockchain, he has led high-impact initiatives for Fortune 500 companies across Energy, Utilities, and Manufacturing. Known for his strategic clarity and hands-on execution, Subhajit focuses on driving Industry 5.0 outcomes—where innovation is human-centric, ethical, and sustainable.

Beyond the boardroom, he is a sought-after voice on global platforms including TEDx, NASSCOM, and IIT, where he shares forward-looking insights on the evolving role of technology in society. With a passion for building purposeful solutions, he continues to mentor startups and advise enterprises on how to navigate complexity with clarity, agility, and impact.

SUBHAJIT SARKAR

But what truly resonated with me was Industry 5.0, a shift from pure efficiency to human-centric, ethical, and sustainable innovation. It’s no longer just about machines working faster; it’s about machines and humans working better—together.

Today, my role has evolved from evangelising technology to enabling transformation—bridging vision with execution, startups with scale, and purpose with performance.

What does Industry 5.0 mean in practical terms for businesses?

While Industry 4.0 was about automation, data, and efficiency, leveraging IoT, AI, AR/VR, and robotics to optimize operations—Industry 5.0 takes a step further.

It’s not just machines doing more now; it’s about machines and humans working together—intelligently, ethically, and sustainably.

In practical terms, Industry 5.0 means:

•Human-centric design: Putting people back at the centre—customisation, creativity, and craftsmanship enhanced by AI and robotics, not replaced by them.

• Resilience over efficiency: Building adaptive systems that can weather shocks—not just run lean. Think decentralised supply chains, digital twins, and predictive insights.

•Sustainability by default: Circular economy models, green tech integration, and regulatory alignment baked into core strategy—not bolted on later.

In short, Industry 5.0 isn’t a rejection of automation but its evolution—a recognition that long-term value comes from aligning technology with humanity, innovation with impact.

How are Gen AI, IoT, and AI/ML reshaping traditional industries like Energy & Manufacturing?

The short answer to this would be: By converging to unlock intelligence at every layer, from the shop floor to the C-suite.

Here’s how it’s playing out in practical and operational terms:

•IoT Real-Time Visibility:

Sensors and edge devices are capturing live data on temperature, pressure, vibration, emissions, and asset health across plants, pipelines, and grids. This is the raw pulse of industrial operations.

•AI/ML

Predictive Optimization:

Machine learning models ingest that IoT data to predict failures, optimise output, and adjust operations autonomously. Downtime is no longer managed—it’s prevented. Quality control becomes very precise.

•Gen AI Human-Machine Collaboration:

Gen AI steps in not to replace engineers or operators, but to amplify decision-making. It translates complex datasets into plain-language insights, drafts maintenance reports, simulates energy mix scenarios, and even guides frontline workers in real time via natural language interfaces.

Example in the Energy & Utilities Sector:

A utility company combines IoT data from smart meters with ML forecasting models to balance grid demand. Gen AI helps operations teams simulate outage scenarios and craft stakeholder communications in seconds. baked into core strategy—not bolted on later.

Example in Manufacturing:

Factories are using IoT-enabled digital twins, where ML predicts machine wear-and-tear, and Gen AI enables engineers to interact with those insights conversationally—accelerating diagnostics and response.

The net results are as follows:

•Smarter operations

•Lower emissions

•Faster decisions

•More empowered humans

This isn’t automation for the sake of efficiency; rather, it’s augmentation for the sake of sustainability.

What role do AI agents play in faster, smarter decision-making in industrial environments?

The answer to this in one word would be: Orchestration.

AI agents are no longer passive analytics tools—they’re becoming active collaborators, capable of observing, reasoning, and acting across complex, high-stakes operations.

Here’s how they’re transforming industrial decision-making:

•Autonomous Monitoring:

AI agents continuously scan IoT data streams from

machines, sensors, and systems—detecting anomalies, safety risks, or performance dips in real time, often faster than any human.

•Contextual Decision Support:

They don’t just raise alerts—they understand context. Is a temperature spike routine, or does it signal a potential failure downstream? Agents synthesise historical trends, maintenan ce logs, and environmental variables to offer insightful recommendations—not just raw data.

•Multi-Agent Collaboration:

In complex environments (think oil rigs or smart factories), swarms of AI agents can coordinate across supply chains, production lines, and logistics—negotiating trade-offs (speed vs. cost vs.

safety) with near-zero latency.

•Human-in-the-Loop Interfaces:

Through Gen AI, agents now speak the language of humans. Engineers can query operational health conversationally; frontline workers receive step-by-step guidance; planners simulate “what-if” scenarios without code.

•Speed-to-Action:

By integrating with enterprise systems (ERP, MES, SCADA, etc.), AI agents can trigger workflows—dispatching a technician, reordering parts, or rerouting logistics without manual intervention.

AI agents are moving from advisory roles to trusted copilots—enabling faster, safer, and more resilient

decisions in environments where seconds matter.

You often speak at platforms like TEDx, NASSCOM, and IIT. What is one key trend or concern you consistently hear from global tech leaders?

Across prestigious platforms like TEDx, NASSCOM, IIT, etc., I often engage with leaders navigating Deep Tech, Gen AI, and Industry 5.0 frontiers. While the excitement is real, so is the undercurrent of caution:

Technology is scaling faster than organisational readiness.

AI agents, autonomous systems, digital twins—they’re ready. But are our governance models, talent strategies, and ethical frameworks keeping pace?

•Speed is no longer the differentiator—alignment is. Tech leaders are now asking: Can we deploy fast, but also responsibly? Can we drive innovation that’s not just cutting-edge, but human-centric, explainable, and sustainable?

• Leadership is being redefined. It’s not just about digital literacy anymore—it’s about digital maturity. Those who can bridge tech fluency with strategic empathy will lead the next wave.

The world doesn’t need more technology for technology’s sake. It needs translators—leaders who can turn disruption into direction and complexity into clarity.

What should business leaders focus on to build a culture that embraces both innovation and human-centric design? Simply speaking—innovation without empathy is just disruption.

The most future-ready companies aren’t just techsavvy—they’re people-savvy.

Here’s what the best leaders focus on:

•Purpose:

Innovation must serve a meaningful “why.” Anchor every initiative—AI, automation, new products, etc.—around who it helps and why it matters.

•Empowerment:

Give teams the freedom to test, fail, and iterate. True innovation thrives in cultures where psychological safety is stronger than hierarchy.

•Cross-disciplinary collaboration:

Bring designers, engineers, frontline workers, and customers to the same table. Human-centric design is a team sport, not a function.

•Metrics that matter:

Track not just ROI, but user delight, employee engagement, and ethical alignment. If you’re only

measuring speed and cost, you’re missing the bigger picture.

As someone who mentors startups and advises Fortune 500s, what is the one piece of advice you would give to today’s tech leaders looking to stay relevant in the present era?

One piece of advice I give tech leaders is this: In an era defined by Deep Tech, Gen AI, and Industry 5.0, tech relevance isn’t just about adopting the latest tools—it’s about understanding where, why, and how they truly fit.

•Avoid the hype trap:

Not every tech wave needs to be surfed. Leaders must ask: What real problem does this solve? For whom?

•Stay contextual:

To your customers, your teams, your ecosystem. The best solutions are rarely universal. They’re hyper-relevant, ethically aligned, and designed with the user—not just the spec sheet.

Whether you’re scaling a startup or transforming a legacy enterprise, your edge lies not in chasing speed—but in cultivating strategic curiosity with grounded clarity.

THE DEEPTECH DECADE:

What Will Define the NEXT 10 YEARS?

As we stand at the dawn of a new technological epoch, it is increasingly evident that the next ten years will be defined not by incremental improvements, but by exponential disruptions. The last decade witnessed the rise of software-driven innovation and consumer-facing digital platforms. The decade ahead, however, will belong to DeepTech—technologies rooted in scientific and engineering breakthroughs that promise to redefine industries, societies, and human potential.

01

Convergence Will Drive the Next Wave of Innovation

The DeepTech decade will be defined by convergence—of biology and computation, quantum physics and AI, material science and sustainability. We will no longer think in silos of biotechnology, artificial intelligence, or robotics. Instead, innovation will occur at the intersection of disciplines. For example, bio-AI interfaces will redefine healthcare diagnostics, while quantum machine learning could open up solutions to currently intractable problems in drug discovery, climate modeling, and logistics.

India, with its demographic dividend and expanding research ecosystem, has the opportunity to be at the forefront of this convergence if it can integrate academia, startups, and government initiatives in a more unified DeepTech ecosystem.

02

AI Will Evolve from Tool to Autonomous Collaborator

Over the next decade, AI will mature from being a productivity-enhancing tool to an autonomous collaborator capable of scientific discovery, creative synthesis, and even strategic decision-making. Large Language Models (LLMs), like GPT and their successors, will be embedded in enterprise workflows, government policy formulation, and national security architectures.

The rise of “agentic AI” — autonomous software agents that can plan, act, learn, and adapt — will disrupt entire sectors from law and finance to logistics and R&D. For India, where enterprise adoption of AI is growing but still uneven, this presents both a challenge and an opportunity to build globally relevant AI governance, ethical frameworks, and talent pipelines.

The Rise of Quantum Advantage 03

Quantum computing is moving steadily from laboratory to application. In the next 10 years, we expect practical

quantum advantage in niche areas like optimization, cryptography, and molecular modeling. This will change the nature of cybersecurity, push the boundaries of materials science, and supercharge AI models trained on massive datasets.

India’s National Quantum Mission, launched in 2023, must now move beyond academic grants to build industrial quantum capacity, partner with global players, and fund indigenous hardware-software stacks. The countries that solve quantum supply chains today will define the cyber-power equations of 2035.

Biotech Will Recode Life as Infrastructure 04

DeepTech in biotech is advancing toward programmable biology. CRISPR, mRNA platforms, synthetic biology, and lab-grown organs are not just scientific marvels; they are infrastructure for the future of health, agriculture, and even climate resilience.

In the next decade, we will see personalized therapeutics, bio-manufacturing of materials, and engineered organisms tackling pollution and carbon capture. India, with its rich biodiversity, pharma expertise, and genomic initiatives like IndiGen, has the raw ingredients for a biotech leap—but it must invest in cross-border research, biomanufacturing zones, and ethical bio-regulation.

05

SpaceTech Will Become the New Strategic Frontier

The DeepTech race for low-earth orbit (LEO), asteroid mining, satellite internet, and deep space exploration will become a geopolitical and commercial battleground. India’s space missions—Chandrayaan, Gaganyaan, and Aditya—are markers of capability, but the next step is commercialization.

By 2035, we will see space-based solar power prototypes, on-orbit manufacturing, and hyper-connected global satellite networks. The Indian private space sector, catalyzed by reforms and ISRO

collaboration, can play a defining role in the global spacetech economy if it focuses on dual-use (civil-military) payloads, launch systems, and downstream applications like earth observation and precision agriculture.

Sustainability Will Be the Litmus Test for DeepTech 06

The DeepTech decade must also be a sustainable decade. Technologies will be judged not only by their disruptive power but by their alignment with climate goals, resource circularity, and social equity. Advanced materials, carbon-negative manufacturing, energy storage innovations, and water purification via nanotechnology will define the DeepTech sustainability frontier.

India, facing the dual burden of development and decarbonization, can lead by piloting cleantech at population scale. DeepTech-led innovations—like AI-optimized smart grids or blockchain-enabled carbon trading—could allow India to leapfrog to a green industrial revolution.

Digital Sovereignty Will Shape Global Alliances 07

As nations realize that control over data, algorithms, compute, and infrastructure is strategic, DeepTech will become central to national identity and global influence. The next decade will witness the formation of new digital alliances, semiconductors becoming policy chess pieces, and a splintering of global tech governance.

India must craft its own digital sovereignty roadmap—investing in indigenous IP, building trusted hardware-software stacks, and creating interoperable standards that are respected globally. Whether it’s IndiaStack for digital identity or BharatGPT for language inclusion, the narrative must move from consumption to creation.

Conclusion: A Decade to Define

The DeepTech Decade will not be passive,it must be engineered, designed, and governed with intention. For India, the time to shift from service-driven IT to science-driven innovation is now. The next ten years offer an opportunity to reimagine national capabilities, build sovereign innovation stacks, and empower a new generation of DeepTech leaders.

This is not just a technological moment,it is a civilizational pivot. Let us rise to it with courage, curiosity, and conviction.

Quantum-Resistant Blockchains: Preparing for the Post-Quantum Era

Much like the printing press or the internet, quantum computing promises to reshape global systems—economic, political, and technological. But in this race toward quantum supremacy, one critical pillar of the modern digital world is in jeopardy: the blockchain. If quantum algorithms can dismantle today’s encryption, what does that mean for digital sovereignty and data integrity?

As quantum computing rapidly evolves from theoretical promise to practical application, it introduces transformative capabilities—along with a serious security threat to the cryptographic foundations of modern digital systems, including blockchain. This growing tension is forcing businesses, governments, and technology leaders to confront a pivotal question: Is blockchain ready for the quantum era?

What Makes Quantum Computing So Powerful?

Unlike classical computers, which use binary bits (0 or 1), quantum computers leverage quantum bits or qubits. These qubits can exist in multiple states simultaneously through a principle called superposition. Additionally, they can exhibit entanglement—where two qubits are interlinked in such a way that the state of one instantly influences the state of another, regardless of distance.

This quantum behavior enables the execution of complex calculations at unprecedented speeds. A prime example is integer factorization—a task that underpins much of modern cryptography. While classical algorithms take years to break strong encryption, quantum algorithms like Shor’s can

potentially solve these in minutes, rendering current encryption schemes vulnerable.

The Quantum Threat to Blockchain

Blockchain technology relies heavily on cryptographic algorithms like RSA and ECC (Elliptic Curve Cryptography) to ensure secure transactions, data immutability, and user authentication. These cryptographic methods are designed to be computationally infeasible to break using classical methods. However, quantum computers could undermine this security paradigm.

Shor’s algorithm, developed in 1994, demonstrates that a sufficiently powerful quantum computer could factor large integers exponentially faster than classical computers. This means digital signatures and private keys used in blockchain could be exposed, enabling attackers to forge transactions, steal assets, or even disrupt entire networks.

Towards Quantum-Resistant Blockchain Systems

To stay ahead of this threat, blockchain developers and cryptographers are actively exploring post-quantum

cryptography (PQC)—algorithms designed to resist quantum attacks while remaining compatible with current and future infrastructure.

1. Lattice-Based Cryptography

Lattice-based cryptography utilizes multidimensional grids of points (lattices) to secure information. Problems like the Shortest Vector Problem (SVP) and Closest Vector Problem (CVP) within these lattices are computationally hard, even for quantum computers. This makes lattice-based systems one of the most promising candidates for quantum-resistant blockchain applications.

2. Hash-Based Signatures

These cryptographic methods use secure hash functions to generate digital signatures. While limited in terms of reusability (often one-time use), hash-based signatures are simple, efficient, and well-understood. They are particularly well-suited for fast-moving blockchain environments and are already being tested in real-world use cases.

3. Code-Based Cryptography

This approach leverages the complexity of decoding randomly generated error-correcting codes. One of the earliest quantum-resistant methods, code-based cryptography offers robust resistance to quantum attacks and is also computationally efficient, making it suitable for blockchain applications like digital identity verification and secure communications.

Practical Implementation and Challenges

While quantum-resistant cryptographic methods show promise, integrating them into existing blockchain networks is no small feat. Most blockchain platforms are built on rigid cryptographic primitives, meaning a full transition would require substantial architectural changes.

A feasible path forward is a hybrid approach—where networks support both classical and post-quantum algorithms. This gradual migration strategy minimizes

disruption while fortifying networks against future threats.

Compatibility and Scalability

Transitioning to quantum-safe algorithms also brings challenges in terms of performance, key size, and computational load. Some post-quantum schemes require significantly larger keys or longer processing

Regulatory and Compliance Outlook

Governments and regulatory bodies are beginning to take note. As the specter of quantum computing looms, there’s increasing recognition of the need for quantum-resilient cryptography, especially in financial systems that rely heavily on blockchain.

Compliance with future-proof security standards is likely to become a prerequisite. Regulatory frameworks are expected to mandate the adoption of quantum-resistant technologies for any digital asset platform operating within critical infrastructure or

Real-World Projects Embracing Quantum Safety

Several pioneering blockchain projects are already testing quantum-resistant cryptography:

•Quantum Resistant Ledger (QRL): Built from the ground up using hash-based signatures to protect against quantum threats.

•IOTA: Employs the Winternitz One-Time Signature Scheme (W-OTS), a post-quantum secure method, for its tangle-based architecture.

However, since full-scale quantum computers are still in development, these systems haven’t yet faced real-world quantum attacks. Continued testing and validation are necessary to prove their efficacy under quantum conditions.

Ethical and Legal Considerations

As with any emerging technology, quantum computing also presents ethical challenges. Access to quantum resources may be limited to a few powerful entities, raising concerns about monopolization and data

Moreover, blockchain systems that adopt quantum-resistant algorithms early could gain competitive advantages, leaving others exposed. This raises questions about digital equity, fair access to security technologies, and the role of government in ensuring a level playing field.

A Call for Proactive Innovation

The convergence of blockchain and quantum computing marks a historic inflection point in digital security. While quantum computers have the potential to disrupt the cryptographic underpinnings of blockchain, the industry is not powerless. Through quantum-resistant cryptography, blockchain developers have the opportunity to re-architect trust and resilience into decentralized systems.

As quantum technology accelerates, the blockchain community must proactively build defenses, engage regulators, and foster collaborative innovation to ensure secure and scalable systems for the future.

The clock is ticking, but with foresight and coordinated effort, blockchain can remain a pillar of digital trust—even in the quantum era.

SpaceTech 2.0 The DeepTech Race to Colonize Orbit and Beyond

The 21st century is witnessing the emergence of SpaceTech 2.0—a profound shift from government-dominated space exploration to a new era driven by deep technology, private innovation, and global ambition. This isn’t just about reaching space; it’s about colonizing low-Earth orbit (LEO), harnessing extraterrestrial resources, building space-based infrastructure, and eventually settling on the Moon and Mars.

Where SpaceTech 1.0 was about symbolic milestones—Sputnik, Apollo, the International Space Station—SpaceTech 2.0 is about building sustainable ecosystems in orbit and beyond, powered by DeepTech breakthroughs in AI, quantum sensing, additive manufacturing, advanced propulsion, and bio-regenerative life support systems.

with LEO commercialization, satellite constellations, space tourism, and orbital services driving the next wave of growth.

The New Space Economy: More Than Rockets

At the heart of this renaissance is the commercialization of space, where government agencies such as NASA, ESA, and ISRO are now collaborating with private players like SpaceX, Blue Origin, Rocket Lab, and dozens of emerging space-tech startups. The global space economy, estimated at $546 billion in 2023, is projected to exceed $1 trillion by 2035,

However, this isn't just about launching satellites. We are entering a new strategic race to build infrastructure in space—autonomous space stations, lunar mining outposts, asteroid refueling depots, and Mars-bound biospheres. And DeepTech is the enabler.

DeepTech: The Engine Behind Space Colonization

1. Advanced Propulsion and Reusability

Traditional chemical propulsion is being augmented by electric propulsion systems such as Hall-effect thrusters and ion engines. Companies are also exploring nuclear thermal propulsion to shorten deep-space travel times significantly. SpaceX's Starship, for instance, represents a dramatic leap in reusability and payload capacity, enabling cost-effective mass transport to orbit and beyond.

2. AI and Autonomy

Autonomous systems are essential for deep space missions where latency makes real-time control impossible. AI-driven spacecraft can conduct self-repair, adaptive navigation, and anomaly detection. On Mars, NASA's Perseverance rover already uses

onboard AI for terrain navigation—paving the way for fully autonomous robotic colonies that prepare habitats for humans.

3. 3D Printing and On-Site Manufacturing

One of the greatest constraints in space colonization is supply logistics. DeepTech startups like Redwire Space and Made In Space are pioneering zero-gravity 3D printing, enabling the in-situ construction of habitats, tools, and spare parts on the Moon or Mars using regolith or recyclable materials. This drastically reduces launch payload costs and improves mission resilience.

4. Biotech and Closed-Loop Life Systems

Sustaining life in orbit or on distant celestial bodies requires self-contained life support systems. Innovations in synthetic biology, hydroponics, and microbial engineering are creating the foundations of regenerative space agriculture and oxygen-recycling ecosystems. Research on bioengineered microbes to produce food, fuel, and medicine from local resources is underway, moving us toward true planetary sustainability.

5. Quantum and Hyperspectral Sensing

From asteroid composition mapping to dark matter detection, advanced sensing technologies are revolutionizing our understanding of space. Quantum sensors, which can detect minuscule changes in gravity or magnetic fields, are being developed for planetary exploration and navigation. These tools also have critical military and dual-use implications, adding urgency to the global tech race.

Strategic Imperatives: Space as the New Geopolitical High Ground

Space is not merely a frontier of exploration—it’s becoming the ultimate geopolitical domain. Nations are racing not just to explore, but to claim, govern, and exploit. The U.S., China, India, the EU, and now private entities are accelerating national space programs with a focus on sovereignty, security, and economic returns.

The Artemis Accords—a U.S.-led framework for lunar governance—have created a coalition of spacefaring democracies, while China and Russia are pushing for an

The Role of Emerging Markets and the Private Sector

Space colonization also raises profound ethical questions: Who owns the Moon? Should Mars be terraformed? What are the rights of AI-based life systems in autonomous habitats? How do we ensure equitable access to space resources?

There is an emerging call for Space ESG , a framework to align space activities with environmental, social, and governance principles, ensuring the space economy evolves responsibly.

The nations and companies that master the DeepTech stack will not just access space—they will define the economic, strategic, and ethical boundaries of the next human frontier. Colonizing orbit and beyond is no longer a dream; it is a technological, geopolitical, and existential imperative.

As Earth grapples with finite resources, climate volatility, and geopolitical fragmentation, space offers not just an escape, but a chance to reimagine civilization. SpaceTech 2.0 is the scaffolding of that vision and DeepTech is the architect.