Building India’s Deep-Tech Stack

• 05 Feb 2026

This editorial is based on “A budget for the deep tech ecosystem & the mitras building it” which was published in The Hind businessline on 02/01/2026.The article highlights India’s shift toward building a full-stack deep-tech ecosystem through strategic policy and infrastructure support. It also examines key challenges and reforms needed to scale deep-tech innovation.

For Prelims:ADITI  scheme, BioE3 policy,National Quantum Mission, IndiaAI Mission 

For Mains:What is deeptech, current development in deeptech ecosystem, key issues and Measures needed to strengthen deeptech ecosystem.

India’s deep-tech ecosystem is no longer driven by isolated startups or subsidy-led innovation, but by a deliberate attempt to build end-to-end technological capability. The focus has shifted from software-only strengths to strategic domains such as semiconductors, AI infrastructure and advanced manufacturing, where scale, skills and supply chains matter as much as capital. Recent policy signals reflect a move from consumption-led digitisation to production-linked, capability-centric growth. This transition positions deep tech as both an economic lever and a strategic asset for India. 

What is Deep Tech?  

• About: Deep tech refers to technologies that are rooted in fundamental scientific research and advanced engineering, aimed at solving complex, large-scale problems rather than enabling incremental or convenience-based solutions.  
  • Unlike conventional digital startups that rely mainly on business model innovation, deep-tech ventures are built on breakthroughs in disciplines such as artificial intelligence, semiconductors, biotechnology, advanced materials, robotics, quantum computing, and clean energy. 
• Core Characteristics of Deep Tech 
  • Science- and research-intensive: Deep tech is anchored in original R&D, often emerging from laboratories, universities, or long-term industrial research. 
    • Progress depends on advances in physics, chemistry, biology, mathematics, and engineering rather than rapid market iteration alone. 
  • Long gestation and high risk: Development cycles are long, capital-intensive, and uncertain. Returns accrue over years, not quarters, making patient capital, state support, and mission-oriented policy critical. 
  • Hard-to-replicate advantage: Deep tech creates durable competitive moats through intellectual property, tacit know-how, manufacturing capability, and system-level integration, unlike easily replicable software platforms. 
  • Infrastructure and ecosystem dependence: Success requires specialised infrastructure, fabs, clean rooms, data centres, testing facilities, along with skilled human capital and resilient supply chains. 
• Common Fields Associated with Deep Tech: Deep tech spans many industries, but it is most prominent in: 
  • Advanced Materials: Developing new polymers, nanomaterials, or battery technologies. 
  • Biotechnology: Synthetic biology, genomics, and drug discovery. 
  • Artificial Intelligence: Advanced machine learning algorithms (beyond simple chatbots) and computer vision. 
  • Robotics and Drones: Automation for agriculture, manufacturing, or logistics. 
  • Quantum Computing: Creating next-generation processors that solve problems standard computers cannot. 
  • Space Tech: Satellite technology, rocketry, and space exploration equipment.
• Deep Tech vs. Shallow Tech 

Feature	Deep Tech	Shallow Tech
Focus	Scientific breakthrough	Business model innovation
Risk	Primarily technical + capital risk (will it work at scale?)  Technical risk (Will it work?)	Primarily market + execution risk (will users adopt?)  Market risk (Will people buy it?)
Time to Market	Long (years to decades)	Short (months to years)
IP Protection	High (Hard to copy)	Low (Easy to copy)

What is the Regulatory Framework Governing Deep-tech in India? 

• Data, Digital & AI Governance 
  • Digital Personal Data Protection Act, 2023: Regulates collection, processing, and cross-border flow of personal data, directly impacting AI, big data, and platform-based deeptech firms. 
  • IndiaAI Mission (policy framework): Sets norms for responsible AI and aims to establish indigenous AI models that align with global standards while addressing unique challenges and opportunities 
• Intellectual Property & Innovation Protection 
  • Patents Act, 1970: Core framework for protecting deeptech innovations in AI, biotech, semiconductors, and materials science. 
  • National IPR Policy, 2016: Encourages faster patenting, commercialisation, and industry–academia collaboration, critical for deeptech scaling. 
• Startup, Investment & Capital Regulations 
  • Startup India Initiative:  Provides regulatory exemptions, tax incentives, and fast-track IP support for deeptech startups. 
    • The government has removed the condition of three-year existence for deep-tech startups to avail recognition under DSIR’s Industrial Research and Development Promotion Program. 
  • Securities and Exchange Board of India (SEBI) Regulations: Govern venture capital funds, AIFs, and emerging frameworks for startup listings and exits. 
  • National Deep Tech Startup Policy (Draft): It is a proposed framework to foster high-tech innovation by addressing challenges in funding, R&D, IP, and regulations, aiming to boost India's global competitiveness in areas like AI, semiconductors, and space tech. 
  • Anusandhan National Research Foundation (ANRF): It aims to provide high-level strategic directions for research, innovation, and entrepreneurship in the fields of natural sciences, including mathematical sciences, engineering and technology, environmental and earth sciences, health and agriculture, and scientific and technological interfaces of humanities and social sciences. 
• Strategic & National Security Regulation 
  • National Security Directive on Telecommunication Sector: It mandates that Telecom Service Providers (TSPs) procure equipment only from "trusted sources" and products. 
  • FDI Policy (Press Notes): Screens foreign investment in sensitive deeptech sectors such as defence tech, space, and telecom.  
• Sector-Specific Deeptech Frameworks 
  • Indian Space Policy, 2023: Opens space launch, satellite, and downstream applications to private deeptech firms. 
  • Biotechnology Regulations (DBT & CDSCO): Govern genomics, bio-manufacturing, and health-tech innovations. 
  • Telecom Act, 2023: Updates regulation for next-gen networks and satellite communications. 
  • Production Linked Incentive (PLI) Schemes: Provide regulatory-cum-fiscal support for semiconductors, electronics, advanced batteries, and EV deeptech. 

What are the Current Developments in India’s Deeptech Ecosystem? 

• Sovereign AI Infrastructure & "Compute-as-a-Public-Good": India has decisively moved from being an "AI consumer" to an "AI builder" by treating compute power as critical public infrastructure.  
  • The "IndiaAI Mission" effectively democratizes access for startups, preventing a monopoly by global tech giants and enabling the training of indigenous Large Language Models (LLMs) that capture India's linguistic diversity and unique cultural datasets, which global models often fail to represent. 
  • The national compute capacity crossed 34,000 GPUs, accessible to startups at subsidized rates.  
    • Indigenous models like Sarvam-1 are being deployed in India to create a sovereign AI ecosystem and reduce dependence on foreign APIs. 
• Operationalization of Semiconductor Fabs: The narrative has shifted from "planning" to "execution" with India's first commercial semiconductor fabs nearing production, effectively plugging India into the global chip value chain.  
  • This transition reduces strategic vulnerability in electronics manufacturing and creates a domestic "multiplier ecosystem" for fabless design startups who can now prototype locally rather than waiting for slots at Taiwan's TSMC. 
  • The Tata Electronics fab in Dholera initiated equipment installation in late 2025, with the first commercial 28nm chips expected by late 2026.  
    • Simultaneously, the facility has opened for "tape-outs" for Indian startups, supporting chips in the 28nm-90nm range. 
• Privatization of Space Launch Services: The Indian space sector has successfully transitioned from an ISRO-monopoly to a commercially vibrant "Space 2.0" economy, driven by the deregulation of FDI and technology transfer.  
  • This has allowed private players to capture a slice of the lucrative global launch market, moving beyond just satellite manufacturing to offering "launch-on-demand" services for small satellite constellations.  
  • For instance, Skyroot Aerospace scheduled its first orbital mission for the Vikram-1 vehicle in early 2026.  
    • At present, the Indian space economy is valued at approximately USD 8.4 billion, constituting a 2% share of the global space market with companies like Agnikul Cosmos commercializing 3D-printed engines for rapid deployment. 
• Institutionalizing Quantum Competence: The National Quantum Mission (NQM) has moved past the policy phase to creating tangible "Thematic Hubs" (T-Hubs) that function as Section-8 companies.  
  • This unique structure allows academic institutions to operate with corporate agility, fostering deep-tech spinoffs in quantum sensing and cryptography that are critical for future-proofing national security against quantum-decryption threats.  
  • For instance, 4 T-Hubs are now fully operational and are engaged in a range of activities including Technology Development, Human Resource Development, Entrepreneurship Development & Industry Collaboration and International Collaborations. 
• Bio-Manufacturing & The BioE3 Paradigm: The BioE3 Policy (Biotechnology for Economy, Environment, and Employment) marks a strategic pivot towards "High-Performance Biomanufacturing" to replace petrochemical-based industries.  
  • By establishing "Biofoundries," the state is enabling a "lab-to-market" pipeline for synthetic biology, focusing on sustainable alternatives like bio-plastics and smart proteins which are crucial for the net-zero transition. 
  • A centralized Biofoundry at ICGEB, New Delhi, is now operational, offering "Design-Build-Test-Learn" services to startups.  
    • The policy supports 6 thematic sectors, helping the bioeconomy reach $165.7 billion in 2024, with a target of $300 billion by 2030. 
• Defense Deep-Tech Indigenization: Recognizing that modern warfare is defined by technology rather than just hardware volume, the MoD has launched aggressive grant mechanisms for "strategic independence."  
  • The ADITI scheme (under iDEX) bridges the "Valley of Death" for deep-tech defense startups by offering substantial risk capital. 
  • It has unlocked ₹750 crore (2023-26), offering grants up to ₹25 crore per startup. Success stories include QuBeats, which received funding to develop GPS-independent quantum navigation systems for the Indian Navy. 
• Green Hydrogen Valleys & Electrolyzer Independence: India is attempting to become a global export hub for Green Hydrogen by localizing the most critical component: the electrolyzer.  
  • By creating clustered "Hydrogen Valleys," the government is ensuring demand certainty (off-take assurance) for deep-tech energy startups, allowing them to achieve economies of scale and compete with cheap Chinese alkaline electrolyzers.  
  • Four "Hydrogen Valleys" were announced by the Union Ministry of Science & Technology with an investment of ₹485 crore, demonstrating the full value chain. Companies like GreenH (manufacturing PEM electrolyzers in Haryana) represent the success of this localization push under the National Green Hydrogen Mission. 
• The Anusandhan RDI Corpus: A major structural fix for the "funding winter" in deep tech is the operationalization of the Anusandhan National Research Foundation (ANRF) corpus.  
  • Unlike typical VC money which seeks quick returns, this sovereign corpus provides "patient capital" essential for R&D-heavy sectors like material science and clean energy, de-risking long-term innovation for private investors.  
  • The Research, Development and Innovation (RDI) scheme with a ₹1 lakh crore financing pool was operationalized by late 2025.  
    • It specifically targets sunrise sectors, offering long-tenure, low-cost funds to scale deep-tech projects that have high technical risk but massive national strategic value. 

What are the Key Issues Associated with India’s Deeptech Ecosystem?  

• The "Valley of Death" in Growth-Stage Funding: While early-stage grants (like iDEX) are abundant, a critical "missing middle" exists for Series B+ growth capital where deeptech hardware startups often die.  
  • Domestic VCs remain risk-averse to long-gestation hardware cycles (5-7 years), preferring the quick returns of fintech/SaaS, forcing premier Indian deeptech startups to flip their headquarters to the US or Singapore to access patient capital.  
  • Even after the operationalisation of the ANRF corpus of ₹1 lakh crore, deep-tech startups receive a disproportionately low share of venture capital, while hardware startups face longer and more uncertain growth-stage funding cycles than software-based firms. 
• The "L1" Procurement Paralysis: The biggest potential customer for deeptech (the Government) remains trapped in the "Lowest Bidder" (L1) procurement archaic framework.  
  • Despite the intent to buy innovative solutions, the bureaucratic machinery lacks the technical capacity to evaluate "Quality-cum-Cost" (QCBS), often disqualifying superior indigenous deeptech products because they cannot compete on price with mass-produced, inferior legacy alternatives or dumped imports.  
  • A December 2025 NASSCOM report noted that more pre-revenue startups are facing operational difficulties after receiving government grants like iDEX, BIRAC, or TDB.  
    • This is termed the "grant liquidity trap," where approved funding is not always available when needed most, restricting the working capital of startups that lack existing revenue 
  • For instance, iDEX had signed 430 contracts with 619 startups and MSMEs. While this shows active engagement, it does not specify the percentage of these that have transitioned into long-term commercial procurement contracts versus initial prototype R&D grants. 
• The "Lab-to-Land" Commercialization Disconnect: India faces a "Productization Deficit" where record-breaking patent filings are not translating into commercial products due to rigid IP sharing norms in academia.  
  • Professors and scientists at IITs/CSIR labs lack the incentives or legal "safe harbor" to spin off companies, leading to a situation where breakthrough research gathers dust in journals rather than creating economic value in the market.  
  • While India ranked 6th globally in patent filings in 2025, the commercial exploitation of patents remains significantly lower than global leaders like the US. 
    • Also, in India, it takes about 58 months on average to dispose of a patent application as compared to about 20 months in China and 23 months in the US. 
• Critical Component Import Dependency: The "Make in India" hardware ecosystem is severely vulnerable to geopolitical supply chain shocks as it still relies on imported "intermediaries" like sensors, precision motors, and specialized gases.  
  • Startups are often just "system integrators" rather than "component manufacturers," meaning a single trade restriction by China or Taiwan can ground entire fleets of Indian drones or robotics. 
  • At present, India imports roughly 90–95 percent of its semiconductor and electronics components, with major suppliers including China, Malaysia, Taiwan, Thailand, and Singapore. 
• The "PhD Talent" & R&D Skills Gap: There is an acute shortage of "Deep-Science" talent capable of bridging the gap between theoretical physics/maths and engineering application.  
  • While India produces millions of coders, it produces very few researchers with the PhD-level expertise required for Quantum Computing or AI algorithm design, forcing startups to acquire expensive talent from Europe or the US, inflating their burn rates.  
  • For instance, according to a Stanford report, India recorded the highest global growth in AI talent concentration between 2016 and 2024 at 252%.  
    • However, it still does not feature among the top 15 countries in overall AI talent concentration, a list led by Israel and Singapore. 
• Testing Infrastructure Bottlenecks: Prototyping hardware requires expensive "industrial-grade" testing facilities (wind tunnels, anechoic chambers, radiation hardening labs) which are largely locked inside government PSUs (ISRO/DRDO) with restricted access.  
  • Startups lose precious months waiting for testing slots, slowing their "iteration cycles" and making them uncompetitive against global peers who have faster feedback loops.  
  • For instance, practically every private SpaceTech player (Skyroot, Agnikul, Bellatrix) must queue for access to ISRO’s facilities because duplicating them is financially impossible for a Series A startup. 
• Regulatory Uncertainty in "Gray Zones": Regulation lags behind innovation, creating "Gray Zones" where operating is legally risky for deeptech sectors like Space mining, GenAI liability, or autonomous bio-manufacturing.  
  • The absence of clear liability frameworks (e.g., "Who is responsible if an AI diagnosis kills a patient?") deters large enterprises from adopting deeptech solutions, stifling the B2B market for startups.  
  • For instance, while the Indian Space Policy 2023 allows private players (NGEs) to launch satellites, the long-pending Space Activities Bill has yet to become law. 
    • Similarly, Consumer Protection Act, 2019 holds doctors and hospitals liable for negligence.  
    • However, if an autonomous AI diagnostic tool (e.g., for detecting diabetic retinopathy) misses a diagnosis, the law is unclear: is the doctor negligent for trusting the AI, or is the software vendor liable for a product defect? 
• Valuation Mismatch & IP Collateralization: Indian financial institutions fundamentally lack the ability to value "Intangible Assets" like IP or algorithms, insisting on traditional collateral (land/buildings) for debt financing.  
  • This forces deeptech founders to dilute equity excessively at early stages just to buy equipment, leaving them with little "skin in the game" by Series B, which ironically discourages future investors.  
  • Because patents are intangible, banks often demand a significant cash margin in a Fixed Deposit to provide a Bank Guarantee. This effectively cancels out the benefit of the credit, as startups must already possess the cash they are trying to borrow. 

What Measures are Needed to Strengthen India’s Deeptech Ecosystem ?  

• Operationalizing "Patient Capital" via Sovereign Risk-Guarantees: To bridge the "Valley of Death" where hardware startups fail, the government must establish a dedicated "Sovereign Deeptech Fund-of-Funds" that prioritizes long-tenure investments over quick exits.  
  • Crucially, this fund should offer "First-Loss Default Guarantees" to private VCs, effectively de-risking their entry into high-gestation sectors like quantum or space-tech.  
  • This mechanism shifts the financial paradigm from "risk-aversion" to "risk-sharing," catalyzing the flow of private institutional capital into asset-heavy innovations that require 7-10 years to mature. 
• Mandating "Quality-Cum-Cost" (QCBS) Public Procurement: The state must transition from a passive regulator to an active "Market-Maker".  
  • Implementing a strict Quality-cum-Cost Based Selection (QCBS) framework ensures that indigenous deeptech products are evaluated on performance and lifecycle value rather than just upfront price.  
  • By reserving a "First Buyer" quota in defense and infrastructure projects for startups, the government provides the critical revenue visibility and commercial validation needed for global scaling. 
• Creating a "National Testing Grid" (Lab-as-a-Service): To drastically reduce the Capital Expenditure (CapEx) burden on startups, all public R&D infrastructure (ISRO, DRDO, CSIR labs) should be mapped onto a unified "National Testing Grid."  
  • This digital portal would operate on a "Lab-as-a-Service" model, allowing private startups to book wind tunnels, anechoic chambers, or bio-safety labs on a "pay-per-use" basis.  
  • Democratizing access to these high-value assets accelerates the "Prototype-to-Production" cycle and prevents startups from duplicating expensive infrastructure that already exists. 
• Liberalizing Academic Spin-off & IP Monetization Norms: Unlocking the latent value in universities requires a standardized "Professor-of-Practice" policy that allows faculty to co-found companies without leaving their academic posts.  
  • Simultaneously, a "National IP Exchange" should be created to act as a marketplace for dormant public-funded patents, simplifying licensing agreements.  
  • This fosters a culture of "Translational Research," ensuring that breakthrough scientific papers are converted into commercial entities rather than remaining theoretical assets. 
• Establishing "Thematic Regulatory Sandboxes": For emerging "Gray Zone" technologies like generative AI, space mining, or synthetic biology, the government must notify "Live Regulatory Sandboxes."  
  • These controlled environments grant startups temporary legal immunity to test products with real customers under supervision, bypassing rigid legacy laws.  
  • This "Adaptive Regulation" approach allows policy to evolve in lockstep with technology, preventing the stifling of innovation while simultaneously generating data to frame long-term safety guidelines. 
• Deep-Science Talent & "Industrial PhD" Fellowships: Addressing the scarcity of specialized talent requires launching "Industrial PhD Fellowships" where researchers split their time between university labs and deeptech startup R&D centers.  
  • The government should fund these positions to create a pipeline of "Scientific Founders" capable of bridging the gap between theoretical physics and engineering application.  
  • This initiative creates a "Talent Density" in niche areas like cryogenics and photonics, which is currently the biggest operational bottleneck for scaling hardware ventures. 
• Component-Level Production Linked Incentives (PLI): Moving beyond final assembly, the PLI framework must be expanded to a "Component-Linked Incentive" (CLI) scheme specifically for deeptech intermediaries like sensors, precision actuators, and specialized alloys.  
  • Incentivizing the domestic manufacturing of these critical building blocks insulates the ecosystem from "Geopolitical Supply Shocks" and trade curbs. 
  • This strategy builds a resilient "Sovereign Supply Chain," ensuring that Indian startups are not merely system integrators dependent on foreign raw materials. 
• IP-Backed Financing & Valuation Standards: To fix the credit gap, the financial regulator must codify standards for "IP-Backed Financing," allowing banks to accept patents and proprietary algorithms as valid collateral for loans.  
  • This requires training a cadre of "Technical Valuers" who can accurately assess the monetary potential of intangible assets.  
  • By legitimizing IP as an economic asset class, this measure unlocks debt capital for startups that are "asset-light" in physical terms but "asset-heavy" in intellectual property, preventing excessive equity dilution. 

Conclusion:

India’s deep-tech journey marks a shift from sporadic innovation to strategic capability-building, where technology, talent and infrastructure are being aligned at scale. However, without resolving growth-stage financing gaps, procurement rigidities and commercialization bottlenecks, this momentum risks stalling before maturity. The next phase must see the State act as a market-maker and risk-sharing partner rather than merely a grant-giver. If executed well, deep tech can anchor India’s economic resilience, strategic autonomy and long-term global competitiveness. 

Drishti Mains Question

“Deep technology is increasingly shaping a country’s economic competitiveness and strategic autonomy.” Examine India’s deep-tech ecosystem in this context, highlighting recent policy initiatives and the structural constraints that continue to limit its scaling.

FAQs

1. What is deep tech?
Science-based, R&D-intensive technology solving complex, large-scale problems.

2. How is deep tech different from conventional startups?
It focuses on capability creation, not business-model or app-based innovation. 

3. Which sectors define deep tech in India?
AI, semiconductors, quantum, biotech, space, clean energy. 

4. What is the State’s role in deep tech?
Ecosystem builder, market-maker and risk-sharing partner. 

5. What is the biggest bottleneck for Indian deep tech startups?
Growth-stage (Series-B+) patient capital and procurement rigidity. 

UPSC Civil Services Examination, Previous Year Question (PYQ) 

Prelims: 

Q. Atal Innovation Mission is set up under the (2019)

(a) Department of Science and Technology 

(b) Ministry of Labour and Employment 

(c) NITI Aayog 

(d) Ministry of Skill Development and Entrepreneurship 

Ans: (c) 

---

Mains:

Q. COVID-19 pandemic has caused unprecedented devastation worldwide. However, technological advancements are being availed readily to win over the crisis. Give an account of how technology was sought to aid management of the pandemic. (2020)