Why Deep tech Startups Fail in the Middle, Not in the Lab

Deep technologies rarely fail because of science. Nor do they fail for lack of investor appetite. Most stall in the critical middle stages—after feasibility is established, but before a product can be deployed reliably.

This gap, where technology works in controlled environments but struggles outside them, has long been described as the ‘Valley of Death’. In deep tech, it most often appears between Technology Readiness Levels (TRLs) 4 and 7, when startups move from proof-of-concept to pilots, and from research to commercial reality.

Devised by NASA, TRLs measure a technology’s maturity from basic research to full operational deployment on a 1-to-9 scale.

Interviews with incubator leaders, investors, and founders point to a consistent pattern: public funding underwrites early research, private capital prefers later-stage deployment, and near-real-world operation remains the most exposed.

How Risk Changes Across TRLs

In 2025, more than half of deep tech funding in India flowed into early-stage rounds, even though cheque sizes were small.

Smaller cheques reflect investor willingness to fund pilots and technical validation, not manufacturing, certifications, supply chains, and market expansion that define later TRLs.

“TRL 1–3 is really about research and proof-of-concept, and most of this happens within academia and their labs,” said Natarajan Malupillai, Group CEO of IIT Madras Research Park and the IITM Incubation Cell. At this stage, there’s uncertainty around the underlying science, and investors are unsure whether lab results would translate into real-world applications. As a result, this phase is largely supported by non-dilutive capital through government grants, institutional funding, and mission-led research programmes.

The transition begins at TRL 4–6. “In IIT Madras Research Park, we are seeing several ideas reach the TRL 4–6 stage where successful lab projects are taken up by entrepreneurs to build and test prototypes,” Malupillai told AIM. “This is where they test the idea’s ability to fit real-life, still-limited scenarios. Most are able to decide on a minimum viable product at this stage. Once the MVP is proven, it is about extended validation in a real-world environment (TRL 7-10).”

But it is precisely here that risks multiply.

The Valley of Death: TRL 5–7

“Startups face their toughest challenges during TRL 5–7, the ‘Valley of Death,’ where they move from lab validation to real-world prototypes,” explained Rounak Lodha, Investment Professional at BlackSoil. This phase demands heavy investment in certifications, compliance, supply chains, and customer engagement, forcing a shift from R&D to commercialisation.

Deepak Gupta, General Partner at WEH Ventures, describes it as a chasm between science and revenue. “TRL 4–7 is sometimes called the Valley of Death, as there is a gap between the science and real revenue here, and a few years can fly by. Sometimes a company lingers at TRL 7–8 (advanced technological maturity) while validating reliable, scaled operations. That may take two to three years until reference customers and predictable revenue emerge.”

Sunil Gupta, co-founder and CEO of deep tech company QNu Labs, identifies TRL 6–7 as the most punishing. “This is where capital requirements rise sharply as we expand R&D, build a go-to-market team, scale delivery, and invest in processes—all at the same time,” he said. “We were ahead of the market and had to sustain long R&D cycles while evangelising a new technology in a still-nascent ecosystem.”

Successfully crossing this phase, he added, requires patience, resilience, and strong alignment between technology vision and commercial execution.

How Investors Read TRLs

While TRLs are not a strict checklist, technology maturity strongly influences funding decisions. “Most deep tech investors typically enter at TRL 4–6, when technology progresses beyond research and demonstrates real-world viability through testing and prototype deployment,” Lodha noted. At this stage, market potential becomes visible, even as scaling risks remain high.

Investors, however, look beyond readiness levels. “While TRL is a useful benchmark, investors prioritise IP strength, market potential, and the team’s execution capability,” he added.

Sunil Gupta explained how diligence deepens as startups advance. “Investors engage with industry experts, academia, and domain specialists who can independently validate the science and its long-term defensibility. They look closely at whether the technology can survive real-world conditions, scale reliably, and integrate into existing infrastructure.”

From there, focus shifts to proof of business: how products are bought, deployed, and scaled; whether multiple use cases exist; and how adoption timelines align with market readiness. “Working demos, field deployments, customer pilots, and certifications significantly reduce perceived risk,” he noted.

For Pratip Mazumdar, co-founder and partner at Inflexor Ventures, startups don’t flash on his investment radar in the idea stage. “We enter when there’s early proof of a pilot with a large client or a working prototype with validation. Even if revenue is small, the signal is clear.”

Founders Must Evolve Too

As startups move from TRL 3+ to TRL 7+, founder skill sets must evolve. Research excellence alone is no longer sufficient; product thinking, financial discipline, and market engagement become critical.

“The most profound transition occurs between TRL 4 and 6,” added Vishal Kataria, VP at Ankur Capital. “Founders must shift from an inward-facing R&D mindset to an outward-facing commercial one. The priority expands from technology to product, customer pilots, and market discovery.”

Many academic founders struggle with this shift, necessitating onboarding complementary co-founders or early leadership hires.

Hariprasad C, chief strategy officer of semiconductor company Netrasemi, noted, “Of course, we startups will always be obsessed with the technical capability of what we have envisioned. But along with that, if you are able to bring up the right market relevance of the technology and the uniqueness, it stands out.”

“It doesn’t matter whether you are in a very, very early stage or on the ideation stage; it’s about the vision of how to take it forward from the initial conception level to making it the POC,” he reaffirmed. 

Why Ecosystems Matter More Than Capital

“Funding alone does not determine survival. It’s the depth and diversity of the support system that really makes the difference,” Malupillai says. Incubators improve survival rates by offering shared labs, mentorship, peer networks, and access to mature industries, lowering the hurdle rate for deep tech founders.

Manas Pal of startup accelerator PedalStart echoed the sentiment. “Most early-stage founders don’t just need capital but hands-on execution support across legal, finance, product, growth, and hiring. Our ecosystem is built around co-building, not just connecting.”

Malupillai added that policy-backed structures also play a catalytic role. Multi-strategy funds like SIDBI Fund of Funds and sectoral schemes such as BIRAC’s Biotechnology Ignition Grant reduce early-stage risk and signal credibility, encouraging VCs to co-invest. Increasingly, tri-sector models are emerging where academia retains IP, startups drive productisation, and corporates provide validation and market access.
“This shift from siloed ownership to jointly developed, market-validated innovation distributes risk more equitably,” Malupillai noted. “And it significantly improves the odds of survival.”

Bridging TRL 4–7 requires more than capital; it demands patience engineered into portfolios, founders willing to evolve, customers willing to pilot early, and ecosystems designed to absorb failure without killing momentum. Until that middle stretch is better supported, India’s deeptech breakthroughs will continue to shine brightest only at the edges.

The post Why Deep tech Startups Fail in the Middle, Not in the Lab appeared first on Analytics India Magazine.