Fractal Analytics IPO: 10 Key Things to Know Before the Offer Opens
- 5th February 2026
- 07:00 PM
- 4 min read
Summary
Fractal Analytics will enter the primary market on February 9 as India’s first pure-play AI and analytics listing. With a trimmed issue size, a 12% grey market premium and recent profitability, the IPO has drawn attention—but valuation and client concentration remain key watchpoints.Mumbai | February 5, 2026
Fractal Analytics’ initial public offering (IPO) opens next week, marking a rare public-market entry from India’s enterprise data, analytics and artificial intelligence (AI) space. The company has moderated its issue size and valuation expectations amid cautious investor sentiment toward AI-led business models.
Below are 10 key things from the Red Herring Prospectus (RHP) that investors should know before the issue opens.
1) IPO dates and timeline
- IPO opens: 09 February 2026
- IPO closes: 11 February 2026
- Basis of allotment: 12 February 2026
- Initiation of refunds: 13 February 2026
- Credit of shares to demat: 13 February 2026
- Tentative Listing date: 16 February 2026
2) Price band
The company has fixed the price band at ₹857–₹900 per share, implying a valuation of about ₹14,450 crore at the upper end.
3) Issue size and IPO structure
The total IPO size has been reduced to ₹2,834 crore, down from the earlier plan of around ₹4,900 crore, indicating a more conservative approach to pricing.
The issue comprises:
- Fresh issue: ₹1,023.5 crore
- Offer for sale (OFS): ₹1,810.4 crore
The OFS means existing investors will partially pare their holdings.
4) Fractal Analytics IPO GMP
The grey market premium (GMP) currently stands at ₹105, indicating a potential listing premium of nearly 12% over the upper price band.
Note: GMP is unofficial and should not be the sole basis for investment decisions.
5) About the company
Fractal Analytics helps large global enterprises use data, analytics and AI to improve decision-making across functions such as marketing, risk, supply chain and customer engagement.
Over the past 25 years, the company has built full-stack AI capabilities by combining technology platforms, domain expertise and industry-specific solutions.
Fractal operates through two business verticals:
- Fractal.ai: Core AI services and AI products, largely delivered through Cogentiq, its flagship agentic AI platform
- Fractal Alpha: A portfolio of smaller, independent AI businesses incubated by the group, each run with separate management teams
6) Selling shareholders
The selling shareholders include Quinag Bidco, TPG Fett Holdings, members of the Remala family, and the GLM Family Trust.
7) Where the fresh money will be used
As per the RHP, fresh proceeds will be deployed toward:
- Investments in subsidiaries and debt repayment (₹265 crore)
- Purchase of laptops and IT assets (₹57 crore)
- New office facilities in India (₹121 crore)
- R&D, sales and marketing investments (₹355 crore)
- General corporate purposes
8) Focus on large global clients
The company primarily works with enterprises that have:
- Over $10 billion in revenue, or
- More than $20 billion in market capitalisation, or
- A customer base exceeding 3 crore users
As of September 2025, Fractal had 122 such large clients, up from 107 two years earlier. Its customer list includes global names such as Citi, Costco, Nestlé, Mondelez, Mars, Philips and Franklin Templeton.
9) Financial performance
Fractal Analytics, positioned as India’s leading pure-play enterprise data, analytics and AI (DAAI) company, has delivered steady top-line growth but only recently turned profitable. Revenue increased from ₹1,985 crore in FY23 to ₹2,765 crore in FY25, reflecting expanding global client engagement. On the profitability front, the company narrowed losses from ₹320 crore in FY23 to ₹42 crore in FY24, before reporting a net profit of ₹196 crore in FY25, indicating improving operating leverage, though with a limited earnings track record as a listed candidate.
10) Key risks investors should watch
- Client concentration: Top 10 clients contribute over 53% of total revenue
- Valuation risk: Analysts flag elevated multiples relative to recent revenue growth
- AI insourcing risk: Clients may increasingly build AI capabilities in-house
- Attrition: Employee attrition remains on the higher side compared with peers
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