DTM E55. Building a Deep Tech Focused Rs 702cr Fund and Exploring Deep Tech Shifts - Manish Singhal, pi Ventures

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Manish Singhal is a technologist-turned-entrepreneur-turned-venture capitalist who aspires to help place India on the global DeepTech innovation map through his work at pi Ventures. With over 31 years of experience spanning diverse fields, including the development of cutting-edge technology products on a global scale, mentoring startups, investing in them, and establishing a deep tech venture fund, he brings a wealth of expertise to the table.

Manish has played a pivotal role in advancing technology in India. He contributed significantly to the development of GPS systems for the Indian Army. Furthermore, he made substantial contributions to the MPEG 4 standard, authoring a chapter that played a crucial role in its commercialization, revolutionizing digital media and communication technologies.

Actively engaged in India's startup ecosystem for the past several years, Manish founded pi Ventures in early 2016 with the vision of accelerating the growth of AI startups in India. Prior to that, he co-founded LetsVenture.com, rapidly transforming it into the premier marketplace for startups and early-stage investors in India. Preceding his involvement with LetsVenture, he served as the India country manager for Sling Media Inc, a Silicon Valley-based consumer electronics startup. During his tenure, he spearheaded the establishment of the R&D and product team in India from the ground up, ultimately achieving a successful acquisition.

On today’s episode we discuss,

• The founding story of pi Ventures & its investment thesis

• How pi Ventures helps Deep Tech Startups grow

• Key criteria for investing in Deep Tech startups

• pi Ventures seminal Deep Tech themes report - Deep Tech Shift 2026

• The experience of raising an INR 702 cr fund for Deep tech, remotely during the pandemic

Listen to the episode here,

or on the below platforms

Links & References:

Manish Singhal - smanishsinghal (LinkedIn), @manish_saarthi (Twitter)

pi Ventures - piventures.in, LinkedIn, Twitter

Deep Tech Shift 2026 Report - Link

pi Ventures DeepTech: Emerging Frontiers Mini Blogs - Link

Pronojit Saha, DTM Podcast - pronojitsaha (LinkedIn), @pronojits (Twitter)

Episode Tweet - Link

Show Notes & Summary:

(00:31) Founding story of pi Ventures. What was its motivation?

1. I've had 30 years of experience in the technology domain, starting as a technologist and consistently working on cutting-edge technology.

2. My journey transitioned to mentoring and angel investing around 2010.

3. Recognizing the lack of support for Indian startups, I founded LetsVenture to connect angel investors worldwide with Indian product companies.

4. This experience led me to realize the need for my own fund to support startups more effectively, resulting in the creation of pi Ventures.

5. pi Ventures initially focused on AI product companies but later shifted to a disruptive AI and deep tech investment strategy.

6. Our first fund of $30 million invested in 15 companies, including a space tech venture.

7. We now operate an $85 million fund, with a primary focus on deep tech, including AI, material science, and other non-AI digital technologies.

(4:05) Investment Thesis and Focus Areas

1. The thesis is based on three pillars: solving a global and big problem, using a 10X differentiated technology, and having a capable team.
2. We are open to disruptive ideas across technologies and sectors, including Agritech, space tech, and SaaS manufacturing.
3. We invest early, usually at the seed stage or pre-series A stage.
4. We work with the companies they invest in and provide subsequent backing through networks.

(5:29) pi Ventures: A Catalyst for Growth in Deep Tech Startups

1. We approach startup support with specific philosophies.

2. Our first philosophy is to bring an operating mindset, drawing from our experience in building companies.

3. We acknowledge that founders are experts in their respective technologies.

4. Our primary focus during the early stages (zero to one) is helping founders transition from heavy technology narratives to commercial or business narratives.

5. We provide support beyond product development, including designing ESOP plans and assisting with hiring.

6. Our approach is flexible, and we assist wherever the founder needs help without taking over their operations.

7. We understand that not all areas may require our assistance, but we are always ready to pitch in to the best of our ability when needed.

(9:18) Key Criteria for Investing in Deep Tech Startups

1. It is important for companies to solve a global problem and have a global customer base.
2. Founders should have a unique way of solving the problem and should be innovative.
3. The founding team should have the right technical and go-to-market abilities.
4. Founders should be willing to learn and adapt to challenges.
5. The founding team is an important factor in determining the success of a startup.

(11:09) Positioning of Indian Startups in Solving Global Problems

1. India has transitioned from being known for its talent available for hire to developing its own product engineering capabilities.
2. The SaaS revolution in India has resulted in successful global startups, such as Freshworks.
3. The current transition in technology indicates the emergence of Deep Tech companies in India that solve global problems.
4. Some examples of successful Deep Tech companies include Pixis, Waysa, Niramai, and Agnikul.
5. These promising developments will eventually change the perception of India's technology capabilities.

(14:35) The Visibility of Deep Tech Startups and Media Attention in the Local Indian Perspective

1. Media attention is not important, what matters is the ability to raise money and sell locally
2. Many successful companies prefer to stay out of the media spotlight and focus on their work
3. Deep tech funding is increasing and more funds are looking at technology, but understanding of the technology is a challenge
4. Companies that offer innovative solutions to relevant problems can sell globally successfully
5. Disruptive solutions have a higher chance of being sold than incremental ones.

(16:22) Experience of Raising the INR 702cr Second Fund for Deep Tech Startups

1. Raising funds for AI investments was a challenging and lengthy process.
2. Initially, there was limited knowledge about AI, but now it is more widely recognized.
3. Building a strong portfolio and creating examples of successful AI companies was crucial to gaining investor trust.
4. The second fund also expanded its investment thesis to include material science and physical tech.
5. The fund was raised mainly through virtual meetings during the COVID-19 pandemic, and received significant support from domestic family offices in India.

(19:22) Motivation behind the Deep Tech Shifts 2026 Report

1. We continuously research different themes and release our work to share knowledge.
2. We recently published a series of mini blogs on our website, refreshing our deep tech thesis.
3. We believe in sharing knowledge to learn more.
4. Our Deep Tech Shifts report in 2026 was a result of our research in those sectors.
5. We will continue publishing mini blogs on our website.

(20:45) Exploring the Themes and New Thesis in the Deep Tech Industry

1. AI is becoming more prevalent in products, leading to the need for disruptive technologies in AI infrastructure.
2. Material science is an important area of innovation, especially in finding alternatives to plastic and improving sustainability.
3. Food tech driven by material science, such as creating artificial meats, is a growing field of interest.
4. Digital technologies beyond AI, such as multi-party authentication and security, are also being explored.
5. The intersection of AI and material science is necessary for creating disruptive products, such as generative AI for creating protein structures as antibodies.

(25:59) The Future of Generative AI: Exploring Its Potential and Layers of Development

1. LLMs (Language and Learning Models) are a fast-moving technology that is maturing quickly and going beyond text.
2. LLMs have interesting use cases and can solve non-trivial problems.
3. Companies with AI stacks are utilizing LLMs for tasks like generating synthetic data and automating support for products.
4. Investing in foundational model research is not seen as attractive due to high capital requirements and competition from established players.
5. As LLM technology becomes more widely used, there may be opportunities in evaluation and infrastructure development.

(29:21) "Considerations for Taking a Deep Tech Startup to Success"

1. Each problem is unique, so I don't believe in generic solutions.
2. Differentiate between technology and product when addressing a problem.
3. Deep tech founders should create a business narrative alongside their technology.
4. This narrative helps connect with others and clarifies the path from technology to product.

(31:05) How can deep tech startups position themselves and acquire their first ten customers?

1. Some things that can work for finding initial customers include working with design partners and defining the product alongside them.
2. It is possible to create a minimal viable product along with tech development in some cases, but not always.
3. Get proof of concepts (POCs) with customers as early as possible to gain a clearer focus on the product.
4. Start with a small number of customers, around four or five, until the tech and product are ready to scale.
5. Spend time on creating a good narrative and messaging, as it is important for opening doors and getting feedback on the product.

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