VCs double down on AI-native start-ups

India’s venture capital ecosystem is undergoing a significant shift as investors increase their bets on AI-native start-ups. With deal flow accelerating and capital chasing defensible, AI-first IP, start-ups in this space are emerging as high-conviction bets despite broader funding caution.

Between January and July (till date), AI-focused start-ups raised $527 million across 82 deals, according to data from Venture Intelligence. Some of the largest AI-linked fundraises this year include Netradyne’s $90 million, SpotDraft’s $54 million, and Infinite Uptime’s $35 million rounds, according to Venture Intelligence data.

The data also showed that the maximum VC investment in an AI native start-up is at the seed stage, which raked in $154 million across 60 rounds.

Start-ups are no longer just applying AI; they’re building proprietary models, leveraging vertical-specific data, and creating defensible IP from Day one, noted experts

“Being AI-native isn’t just about using AI — it’s about reimagining the entire product and business model around it. This shift is driving a new level of investor confidence, as AI-native companies demonstrate the potential to scale faster, adapt quicker, and deliver transformative value across industries. Gnani.ai exemplifies this evolution with its Agentic AI-first voice intelligence and Small Language Models, purpose-built for real-time, low-latency enterprise applications,” said Ganesh Gopalan, Co-Founder & CEO, Gnani.ai.

VC firms are sharpening their focus on AI-native start-ups, driven by a combination of faster adoption curves, expanding use-cases, and transformative potential across sectors. Investors see these start-ups not as iterative improvements over SaaS, but as structurally different businesses.

“These companies are demonstrating faster product iteration cycles, leaner teams, and in some cases, better margin profiles due to automation,” said Abhishek Prasad, Managing Partner at Cornerstone Ventures. “They’re not just efficient — they’re structurally different.”

Venture capitalists are also drawn to the greenfield opportunities created by intelligent automation, large language models (LLMs), and domain-specific AI. “The right way to look at these applications is as ‘LLM Apps,’” said Kushal Bhagia, Founder & Partner at All In Capital. “What’s important is whether the AI unlocks a compelling greenfield use-case — human-like front desk automation, deep multilingual research, or domain-specific workflows that compel adoption.”

India’s edge lies in deploying AI for localised pain points rather than training foundational models, with most founders working at the application layer to bring rapid solutions to underserved markets such as legal, healthtech, logistics, and skilling.

AI-native start-ups currently command 3–4x valuation premiums over traditional SaaS companies, noted industry insiders. Investors attribute this to the pace at which these start-ups are hitting growth milestones, expanding addressable markets, and demonstrating potential for long-term operating leverage.

“The premium stems from expectations of quicker customer adoption, exponential scale, and more transformative greenfield use-cases,” said Bhagia of All In Capital. “Many AI-native start-ups hit growth milestones in months, that took SaaS firms years.”

The assumption, some say, is that software-like margins will kick in once compute and power costs decline. “Investors are pricing in eventual software-like margins, assuming compute and power costs will come down in future,” Bhagia added. “But the premium won’t be universal forever — it will persist only for those with defensible moats and real operating leverage.”

Prasad agreed, noting that while the current enthusiasm is justified in part, the market will gradually separate durable plays from hype cycles. “Over time, the market will differentiate between those that are merely AI-wrapped and those that deliver deep proof of value,” he said. “Valuations will correct toward fundamentals — especially unit economics and defensibility.”

“An AI-native startup builds its product and systems around AI from the ground-up. The technology shapes how the product functions, how it improves, and how it solves problems. In these companies, AI is part of the architecture, not just a tool applied later. That approach often allows them to solve problems differently or more efficiently, which is why they tend to attract higher valuations, sometimes 3-4 times more than traditional software companies. But those valuations are based on how defensible the technology is, whether the advantage comes from proprietary data, better models, or a product that keeps improving as more people use it,” said Arpit Mittal, Founder & CEO at SpeakX.AI (Formerly Yellow Class).

The consistent thread across investors is that premium valuations will only sustain for start-ups that can demonstrate strong outcomes, domain depth, and scalable defensibility through data loops, vertical workflows, or ecosystem lock-ins.

Published on July 7, 2025