BENGALURU: India’s agentic artificial intelligence (AI) startups are running into a funding wall. Investors are moving away from “fund the narrative” and focusing on “fund the proof”, backing startups that show revenue traction or unique technology rather than just building applications on existing AI models.
Agentic AI—software designed to carry out specific workflows or tasks autonomously—is drawing investor interest worldwide. These “agents” can plan, make decisions and execute actions with limited human supervision.
Of the 172 agentic AI companies in India, only four have reached Series B and 10 have raised Series A, according to data from Tracxn. Forty-nine are at seed stage, 14 have undisclosed funding, and 95 haven’t raised any capital.
“India sits squarely in a seed-heavy, Series A bottleneck phase,” said Santosh Tiwari, partner, transaction strategy and execution at EY-Parthenon. “The era of ‘fund the narrative’ in agentic AI is giving way to ‘fund the proof.’”
Most of the funding crunch comes from India’s focus on startups that build on top of global AI models from OpenAI, Anthropic and Google. That makes sense locally, thanks to India’s engineering talent and low costs. But investors abroad want something harder to copy—strong intellectual property or specialized solutions—which many Indian startups don’t yet have.
“When we started investing in the GenAI era we looked for companies with solid differentiation,” said Alok Goyal, partner at early-stage fund Stellaris. “We were very cautious back then and took our time to build our thesis.” Through 2025, Stellaris invested in six agentic AI startups, including underwriting services startup Pibit’s $7 million Series A and voice-based sales agent Arrowhead’s $3 million seed round.
Stellaris sorts agentic AI into a few types: agents that can do work without being fully accurate, human-in-the-loop services, enterprise-focused solutions, and voice agents. “Agentic AI is a lot more real today than it was a year ago,” Goyal said.
The SaaS squeeze
But even as these startups experiment with different agent types, many face stiff competition from established players that are rapidly adding AI-powered products. Startups must build technology that can’t easily be replaced by large language models while also generating revenue and scaling.
“There’s the SaaS and software companies that are building on top of AI models and launching agentic solutions to their customers. They’ll be at par with the application layer companies,” said Atul Gupta, managing partner at Trident Growth Partners.
Data from Venture Intelligence shows the top 10 large deals across 2025 and 2026 so far went to established SaaS players like Innovaccer, Uniphore, UnifyApps and Fractal Analytics.
Last week, Fractal launched Flyfish, an agentic platform for B2B sales, while Innovaccer now builds agentic solutions for healthcare in the US, raising $275 million in January 2025 from B Capital Group, M12, and others.
Still bullish
Despite these challenges, investor interest in agentic AI remains strong. Global funding rose to $6.4 billion in 2025, up from $4.8 billion in 2024, according to Tracxn. But investors remain divided over whether startups should build broad platforms or focus on niche solutions.
“Our thesis a couple of years ago was that there will be specialised space. But we’re uncovering that horizontal platforms are able to gobble these up totally,” said Goyal. “However, classic business applications need application integrations because process and work can sometimes be very specific to individual companies.”
Horizontal platforms like Lovable, Emergent, Replit and Rocket.new cater to prosumers and builders. Lyzer and Kogo.ai, offer a ‘marketplace’ which allows companies to shop for and then integrate agents into workflows, with Lyzer recently raising $14.5 million at a $250 million valuation from and Rocketship VC.
Lightspeed-backed Gushwork has opted to go the niche route and uses AI agents to help small and medium businesses generate leads, raising $9 million in seed funding from Susquehanna Asia VC. “We’re super opinionated as a software. Our agents work in a particular way to deliver a particular outcome for a larger industry,” said co-founder Nayrhit Bhattacharya. “We believe that while the use case is niche, the market is much larger.”
Valuation mismatch
Even with promising examples, many startups are struggling to meet investor expectations. Deal flow is strong, but valuations are proving tricky. Many ask for $15-30 million based on demos but have little revenue to show. Companies with proven enterprise revenue in sectors like healthcare, finance, and supply chain are more likely to close deals.
“Agentic AI companies are asking for valuations in the 20–50x revenue range, benchmarked against the most elite AI companies globally,” said EY-Parthenon’s Tiwari. “But most of these companies lack the cohort maturity, gross margin profile, and retention data that would justify those multiples.”
As a result, investors in India push back hard on pricing, given the market’s capital availability, risk appetite and longer enterprise sales cycles.