Deep Tech and AI Investing in India: Current and Future States
Abstract
The panel opened with brief introductions and a data‑driven overview of deep‑tech investment in India, highlighting a 12 bn share for AI. Speakers examined the impact of the government‑backed RDIF (R‑D Innovation Fund), the evolving role of domestic private capital, the emergence of family‑office funding, and the need for patient, policy‑aligned capital. The discussion also covered ecosystem‑building initiatives (IDTA commitments, university‑industry linkages), sector‑specific opportunities (AI for agriculture, robotics, quantum, multilingual LLMs) and the challenges of scaling deep‑tech ventures globally. The session concluded with a rapid‑fire audience Q&A and closing remarks emphasizing a “zero‑to‑one” innovation moment for India.
Detailed Summary
- Gopal Jain opened the session, noting Gaja Capital’s 27‑year history of growth‑stage investing and its co‑founding role in the Indian Deep‑Tech Investors Association (IDTA). He mentioned the firm’s “Gaja Gives” programme that supports university‑level deep‑tech research.
- Siddharth Pai (identified in the transcript as “Siddharth Bhai”) introduced himself as founding partner of T1P Capital, a VC focused on technology‑enabled companies and deep‑tech. He highlighted his work on regulatory affairs, his chairmanship of the Indian Venture Capital Association (IVCA), and his role on SEBI’s APEX policy‑formation body.
- Nishith Desai introduced his law firm’s long‑term focus on futuristic technologies, emphasizing foresight on legal, tax and ethical issues that will arise 10‑20 years ahead.
- Sudhir Sethi (Chiratae Ventures) referenced a decade of deep‑tech investments totaling roughly $300 m and described the panel’s informal “floor‑seating” arrangement, inviting younger founders to sit at the front.
- Vardaan Ahluwalia (Premji Invest) and Sneh Vaswani (Miko) joined later, each affirming their commitment to deep‑tech as a strategic priority.
2. State of Deep‑Tech Investment in India
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Key Data (presented by the moderator/IDTA)
- Since 2015, >1,200 deep‑tech companies have attracted ≈ $28 bn in total investment.
- AI‑focused deals account for ≈ $12 bn of that total.
- In 2025, projected deep‑tech funding is 2 bn, is AI).
- 70 % of deep‑tech capital is allocated to growth and late‑stage rounds.
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Report Launch
- The panel announced the release of India’s first Deep‑Tech Report (co‑authored with Venture Intelligence) scheduled for 3 pm on the day of the summit.
3. Capital Reality Check – The RDIF & Private‑Sector Dynamics
| Speaker | Main Points |
|---|---|
| Siddharth Pai | Described three macro‑level shifts: 1️⃣ LP appetite for long‑gestation deep‑tech funds has risen, driven by confidence that Indian IPOs can deliver hard cash. 2️⃣ R‑D Innovation Fund (RDIF) is bridging research‑to‑commercialization, providing up to 50 % of deep‑tech funding via grants across Technology Readiness Levels (TRL). 3️⃣ Ecosystem maturity – talent depth and VC platform teams now offer non‑financial support (product, regulatory, hiring). He warned that the ₹1 lakh crore (~$11 bn) RDIF programme will need 5‑7 years to fully deploy and that results will materialise over a decade. |
| Gopal Jain | Noted that Indian venture capital has grown from ≈ 40 bn/yr today, with ≈ 100 bn) and the US ($150 bn), India still trails but is on a upward trajectory. Emphasised the need for public‑sector catalysts (RDIF, National Semiconductor Mission, Quantum Mission) to address market failure and spur private‑sector co‑investment. |
| Vardaan Ahluwalia | Highlighted Premji Invest’s role as a family‑office investor, stressing the importance of patient capital and the emerging “poster‑child” narrative for Indian deep‑tech. |
| Chris (IDTA) | Stressed that family offices and high‑net‑worth individuals are now setting up larger AIFs (Alternative Investment Funds) capable of making sizeable late‑stage checks. Mentioned that the RDIF’s ₹20 000 crore/year deployment target requires an equivalent private‑sector contribution (≈ ₹80 000 crore/yr) to achieve the 50/50 split. |
| Sudhir Sethi | Reiterated that deep‑tech requires long gestation; current capital pipelines are insufficient for the scale required. Cited IDTA’s $2 bn commitment from member funds over three years as a concrete example of private‑sector momentum. |
4. Founder‑Centric View – Raising Capital in Deep‑Tech
- Sneh Vaswani (Miko) described a ten‑year journey that began with zero revenue and 500+ rejections before securing family‑office and institutional back‑stop funding.
- She highlighted the rise of Indian family‑office capital: half of Miko’s cap‑table now comes from families, offering long‑term patience and hands‑on mentorship (e.g., strategic guidance, follow‑on funding).
- Noted that U.S. market exposure has improved, with Indian‑origin AI startups achieving 10× revenue‑multiple exits at $100 m revenue levels, making them attractive to U.S. investors.
5. Legal & Regulatory Perspectives
- Nishith Desai stressed the need for forward‑looking legal frameworks to anticipate tax, ethical, and IP challenges of deep‑tech.
- He advocated for policy scaffolding that balances encouraging innovation with protecting against “bad actors.”
6. Policy & Ecosystem Recommendations
| Speaker | Recommendations (next 6‑12 months) |
|---|---|
| Nishith Desai | 1️⃣ Create clearer IP‑ownership rules for university‑spin‑outs. 2️⃣ Introduce tax incentives for grant‑based research that do not treat grants as taxable income. |
| Siddharth Pai | 1️⃣ Strengthen grant‑to‑commercialization pipelines (e.g., via RDIF). 2️⃣ Formalise platform‑team support within VCs to reduce founder burden. |
| Gopal Jain | 1️⃣ Encourage larger domestic AIFs to meet RDIF absorption capacity. 2️⃣ Promote success‑story dissemination to attract LPs. |
| Chris | 1️⃣ Scale family‑office AIFs to enable larger checks. 2️⃣ Streamline application processes for RDIF disbursement (targeting a 3‑month fund‑to‑company timeline). |
7. Application‑Layer Opportunities
- Panel consensus that deep‑tech underpins AI‑enabled agriculture, healthcare, education, automotive, and multilingual LLMs.
- Quantitative insight: if the foundational deep‑tech market is valued at ≈ 1 bn).
- Examples cited:
- Mossip (open‑source identity platform) operating in 29 countries serving >300 m users.
- Diksha (education platform) expanding from Indian schools to African markets.
- 2D‑materials & analog computing for “green AI”.
8. Audience Q&A – Rapid‑Fire Segment
| Questioner | Topic | Summary of Answer |
|---|---|---|
| Audience (Unnamed) | Exit routes – M&A vs IPO | Sudhir Sethi: M&A will become a major exit channel as deep‑tech firms mature; current Indian M&A activity is modest but expected to grow. |
| Audience (Unnamed) | Agriculture AI – scaling solutions for small farms | Chris: AI can drastically improve farm productivity and reduce post‑harvest loss; early‑stage ventures are already attracting capital. |
| Audience (Unnamed) | Capital for founders without decks | Panel consensus: Exceptional founders (3–4 σ above the norm) may receive “blind‑pitches” from family‑office investors; otherwise a solid deck remains essential. |
| Audience (Unnamed) | Team size vs AI‑augmented efficiency | Sudhir Sethi: Team competence matters more than headcount; AI can reduce personnel needs but does not replace the need for domain expertise. |
| Audience (Unnamed) | Future funding thresholds (2026‑27) | Vardaan Ahluwalia: Funding size will depend on product‑market fit and capital efficiency; AI‑driven automation can lower burn‑rate but does not guarantee lower raises. |
9. Closing Remarks
- Gopal Jain reiterated that India is at an “innovation moment”, moving from frugal “jugaad” to purposeful “boring through” deep‑tech creation.
- Premji Invest pledged continued support for IDTA and deep‑tech ecosystems.
- Moderators thanked METI, IDTA, and the audience, and announced that the panel would remain available for informal follow‑up discussions after the session.
Key Takeaways
- Deep‑Tech Investment Landscape – Since 2015, India has attracted 12 bn.
- RDIF as a Catalyst – The government‑backed R‑D Innovation Fund aims to commit ₹1 lakh crore (~$11 bn) over several years, targeting a 50/50 split with private capital.
- Private‑Sector Momentum – Domestic VC‑funds, family offices, and IDTA members have collectively pledged $2 bn for deep‑tech over the next three years; large AIFs are emerging to meet RDIF absorption needs.
- Policy Gaps & Recommendations – Immediate actions needed include clarifying IP & tax treatment of grants, strengthening research‑to‑commercial pipelines, and building platform‑team support within VCs.
- Founders’ Experience – Successful deep‑tech founders (e.g., Miko) now rely heavily on family‑office capital, which offers patient, long‑term funding and mentorship.
- Application‑Layer Opportunity – The downstream market for AI‑enabled products (agriculture, health, education, multilingual LLMs) is ~10× larger than the foundational deep‑tech market.
- Exit Landscape – While IPOs remain a route, M&A is projected to become the dominant exit mechanism for Indian deep‑tech firms as they mature.
- Talent & Ecosystem – Indian deep‑tech talent thrives under frugal innovation, and the ecosystem is shifting from founder‑as‑jack‑of‑all‑trades to specialist teams supported by VC platform services.
- Global Competitiveness – With lower cost of innovation (≈ 1/5 of US) and a large domestic market, India is positioned to become a global deep‑tech hub over the next decade.
- Call to Action – Investors must adopt patient capital frameworks, policymakers need to streamline grant and tax regimes, and founders should focus on building scalable, high‑impact solutions to attract the next wave of deep‑tech capital.
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