India’s deep-tech and artificial intelligence (AI) startup sectors are buzzing with energy, promise, and no small amount of frustration. On August 17, 2025, business leaders, founders, and experts alike recognized the crucial role these startups play in driving the high-tech sector and broader economy forward. The journey, however, is anything but smooth—especially when it comes to scaling up, finding funding, and moving from promising pilot projects to real-world impact.
Names like Grey Orange, Addverb, Cynlr, Ather, Mindgrove, and Agnikul have become synonymous with deep-tech success, especially in the innovation corridors near IIT Madras. Others, including Planys, Solinas, Xyma, and Plenome, have made waves by delivering solutions where none existed before or by shaking up established markets, particularly in the maintenance of physical and digital infrastructure. According to The Hindu, these startups are lauded for their ability to create a strong innovative moat—essentially, a buffer of intellectual property and know-how that helps them fend off competitors and expand internationally.
But the path from idea to impact is a long one. Many founders, especially in deep-tech, find themselves underestimating just how much time (and money) it takes to transform a proof of concept into a product that can survive in the real world. While research and development (R&D) funds are often available to get a concept off the ground, turning that concept into a robust, field-ready product is another matter entirely. Testing, validation, and redesign—often based on feedback from real users—can take years. And it’s not just the technology that needs work. Founders must also grapple with standardization, reliability metrics like mean time between failures (MTBF), and ergonomic considerations, all of which require specialized resources that aren’t always easy to find.
“Many founders report that after initial recognition, startups develop well-structured pilot projects… but face significant hurdles when attempting to scale in real-world conditions,” said Reva Malhotra, consulting director for early-stage startups, as quoted in Mint. The Indian market’s penchant for heavy customization only adds to the challenge. Every new market segment can require a new round of product tweaks, making it difficult for startups to justify the expense of development when there’s no guarantee of immediate revenue.
This is where support structures like pre-incubators, incubators, and venture studios—especially those linked to universities—become indispensable. These organizations offer more than just physical space; they provide grants, mentorship, and crucial industry connections. They help startups move beyond the lab and into the marketplace, guiding founders through the maze of product creation, end-user feedback, and industry partnerships.
Government policy plays a pivotal role, too. More grants targeted at scale-up and translational research, along with incentives for industry collaboration, can make all the difference. There’s a pressing need for facilities that allow startups to accelerate product testing, develop reliability metrics, and access agencies dedicated to certification and standardization. As The Hindu noted, programs that bring in targeted end-users for pilot projects could be a game-changer, potentially leading to full-fledged commercial orders for promising startups.
Yet, even with these supports, founders face what some call a “wall of resistance” at the scale-up stage. There’s often a trust deficit when it comes to new solutions, particularly when entrenched approaches have long dominated an industry. This is especially true in states like Tamil Nadu, which is home to a diverse array of industries, multinational back-offices, and global capability centers.
Tamil Nadu, for its part, has made strides in improving access to government schemes and funding through initiatives like Startup TN. But experts say more systemic attention is needed. The state, with its robust industrial base, is ideally positioned to support startups through go-to-market strategies, industry partnerships, pilot programs, and scale-up initiatives. The Tamil Nadu Industrial Development Corporation (TIDCO) and Tamil Nadu Infrastructure Fund Management Corporation (TNIFMC) have the potential to provide targeted impact funding and create state-level facilities for product testing and standardization—moves that could make a world of difference for local startups.
In the AI sector, the story is much the same—brimming with potential, but hamstrung by structural barriers. Despite recognition from bodies like the Department for Promotion of Industry and Internal Trade (DPIIT) and access to schemes such as the Startup India Seed Fund Scheme (SISFS) and Credit Guarantee Scheme for Startups (CGSS), scaling beyond the pilot stage remains a persistent challenge. As Mint reported, “the Series A+ transition is still the critical drop-off point,” according to Rohan Dani of Blacksoil. Institutional funding is hard to come by, and many startups find themselves stuck at the minimum viable product (MVP) stage due to issues like limited enterprise adoption, poor network access, and the complexities of local language integration.
Private accelerators have stepped in to fill some of the gaps. Google’s AI First Accelerator, for example, has helped startups like SpotDraft, Kroop AI, and Merlin AI raise over $61 million in just six months. But for DPIIT-recognized ventures relying solely on government grants, attracting follow-on capital remains a struggle. “While grants form an important part of the growth equation, they represent only one element in a far more complex framework,” Malhotra explained.
This funding mismatch is prompting many AI founders to look abroad from the very beginning. According to CV Farish of Google, a staggering 93% of Indian AI startups in their accelerator are building for international markets, drawn by better infrastructure and faster adoption rates overseas. Dani pointed to success stories like Qure.ai and Sarvam AI as proof of what’s possible when “government infrastructure, market pilots, and VC capital align.” But he also stressed that if India wants to produce more AI scale-ups, it must bridge the gaps in growth capital, R&D incentives, and market readiness at home.
What’s the way forward? Experts argue for a more coordinated approach: more grants for scaling and translational research, streamlined certification and standardization processes, and stronger bridges between startups and established industries. Programs that give startups access to pilot projects with real users, followed by opportunities to secure full-scale contracts, could help break the cycle of endless pilots and stalled growth.
Tamil Nadu’s industrial diversity—spanning everything from automobiles to electronics—offers fertile ground for targeted initiatives that connect established companies with local deep-tech and AI startups. Such collaborations could be a win-win, driving innovation while supporting the growth of homegrown talent and technology.
India’s deep-tech and AI startup ecosystems may still be works in progress, but the potential is undeniable. With the right mix of policy support, industry engagement, and access to capital, these startups could well become the engines of the next wave of economic growth—both at home and on the global stage.
