Fractal Analytics IPO Upcoming
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About Fractal Analytics
Founded in 2000, Fractal Analytics is an AI-driven analytics company co-founded by Srikanth Velamakanni. The company specialises in AI services and is preparing for an initial public offering (IPO) by FY26. Fractal is known for investing heavily in research and development, using 7-10% of its revenue for R&D and hiring approximately 2,000 people annually to support innovation.
Fractal Valuation
Fractal Analytics is considering filing for an IPO in Mumbai, potentially raising $500 million. The company is focusing on expanding its AI capabilities ahead of the IPO by launching new products like Cogentiq, an agentic AI platform, and Ramanujan, an advanced AI model for reasoning and coding.
Operations & Performance of Fractal
For FY24, Fractal Analytics reported a consolidated net loss of INR 54.7 Cr, contrasting with a profit of INR 194.4 Cr in the previous fiscal year. The net loss was partly due to a loss of INR 21.8 Cr from exceptional items, whereas FY23 saw a gain of INR 494.9 Cr from these items. Despite this, the company’s EBITDA improved, standing at INR 73.4 Cr compared to an EBITDA loss of INR 118.3 Cr in the previous fiscal year.
Fractal’s revenue from operations rose 11% to INR 2,196.3 Cr in FY24 from INR 1,985.4 Cr in FY23. Including other income of INR 45.6 Cr, Fractal’s total income for the fiscal year increased by 10% year-on-year to INR 2,241.9 Cr. On a standalone level, Fractal turned profitable with a profit after tax of INR 123 Cr, a significant recovery from a loss of INR 31.1 Cr in the previous year. The company’s standalone total income was also up, increasing by 12% year-on-year to INR 1,183 Cr.
Future Plans of Fractal
Fractal plans to further advance its AI offerings, having launched products like Marshallgoldsmith.ai, Kalaido.ai, and Vaidya.ai, and aims to introduce new platforms such as Project Pioneer. The company seeks a capital subsidy under the IndiaAI Mission and will allocate funds towards the procurement of high-end graphic processing chips for large language models.