By Ahana Verma 
India’s AI sector finally has a public market reference point. Furthermore, it is a complicated one.
On February 16, 2026, Fractal Analytics listed on BSE and NSE becoming India’s first pure-play enterprise AI company to go public. The IPO raised ₹2,834 crore at a price band of ₹857–₹900 per share. Consequently, Fractal became the benchmark that every AI company in India now gets compared against.
However, the listing was not the triumphant debut that optimists expected. Shares opened flat and closed approximately 6% below the issue price on day one. Therefore, the market sent a clear message: AI conviction alone does not justify any valuation.
What Fractal Analytics Actually Is
Founded in 2000 by Srikanth Velamakanni and Pranay Agrawal, Fractal Analytics is not a new company. Moreover, it is not a generative AI startup. Instead, it is a 25-year-old enterprise AI and analytics firm that powers data-driven decisions for over 100 Fortune 500 clients including Citi, Nestle, and several global healthcare companies.
Its core business spans two segments. First, AI-powered analytics and decision intelligence delivered through its Cogentiq platform. Second, professional services implementation, integration, and custom AI development for large enterprise clients. Furthermore, the company holds 28 registered patents and 38 pending applications across AI, behavioural science, and data engineering.
The financials showed a genuine turnaround. Specifically, Fractal swung from a ₹54.70 crore loss in FY24 to a ₹220.60 crore profit in FY25 a 503% PAT improvement. Additionally, revenue grew consistently. Therefore, the listing was not a distressed exit. It was a calculated timing decision by major shareholders TPG Capital and Apax Partners.
Why the Listing Opened Flat and What It Means
The IPO was subscribed 1.24 times overall modest by Indian IPO standards where popular issues routinely see 50–100x subscription. Moreover, the 64% OFS component flagged a concern that experienced investors recognised: existing shareholders cashing out heavily is rarely a bullish signal for post-listing performance.
Nevertheless, the subscription completed and the listing happened. Consequently, Fractal is now a publicly traded AI company in India. Furthermore, it trades at a premium multiple relative to traditional IT services companies reflecting its positioning as a “pure-play AI growth company rather than a traditional IT services firm.”
Additionally, the subdued listing creates an interesting entry point for long-term investors. Specifically, India’s AI analytics sector is growing at 25–30% CAGR. Furthermore, enterprise AI adoption is accelerating across every major sector. Therefore, the question is not whether Fractal’s market grows. It is whether Fractal can capture enough of that growth to justify its current valuation.
What This Tells Indian AI Founders
Fractal’s listing is the most important data point in Indian AI public markets in 2026. Moreover, it carries several direct lessons for founders thinking about their own eventual exits.
First, profitability matters more than it did in 2021. Fractal’s turnaround from loss to profit was essential for the IPO to proceed. Furthermore, institutional investors looked at earnings quality, not just revenue growth. Consequently, AI founders should treat their path to profitability as a public market readiness metric, not just an operational goal.
Second, the OFS ratio matters. Specifically, an IPO where existing investors are exiting heavily signals to public market buyers that the “smart money” is leaving. Therefore, founders and early investors should consider the balance between primary capital raise and secondary exit when structuring their IPO.
Third, being first has value beyond the share price. Fractal is now a reference point. Furthermore, every analyst, every fund manager, and every future AI IPO in India will be benchmarked against Fractal’s multiples. Consequently, the first mover sets the valuation framework for an entire sector regardless of how the stock performs on day one.
India’s AI public market era has started. Moreover, it started with a lesson in valuation discipline. That is exactly the right lesson to start with.
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Raghav Sharma 
Nayra Roy