Ema raises $77M as AI agents target SaaS spend — SkimNews

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- Ema raised $77M in Series B funding led by Bengaluru-based Creaegis, with Accel, Section 32, and Prosus increasing their stakes, bringing total funding to $140M and more than quadrupling its 2024 valuation (the startup declined to disclose the new figure).
- Ema deploys "AI employees" — systems coordinating multiple AI agents across a company's existing applications — and CEO Surojit Chatterjee said some customers are already replacing large SaaS applications entirely because they're "mostly becoming like a database."
- Ema's platform can draw on more than 150 AI models including frontier and open-source systems, and Chatterjee framed progress at labs like Anthropic and OpenAI as complementary rather than competitive, saying frontier advances are "actually very beneficial to us."
- Ema counts NTT DATA, Hitachi, ADP, PwC, Google, KPMG, Wipro, and Microsoft among customers, with 50+ active enterprise deals, 1M+ active users, and 5M+ actions handled; revenue grew 50-fold over two years and bookings surpassed $150M, with net dollar retention around 180%.
- Ema maintains gross margins near 80%, charges customers based on completed tasks rather than seats or tokens, and Chatterjee said IT services firms are now working with Ema because their "human-forward model may not be the best model going forward."
- Ema plans to use the new capital to expand go-to-market operations, particularly sales and marketing, after years spent building the product; the 200-employee, Mountain View-headquartered startup will push into Asia-Pacific, South America, and parts of the Middle East.
Why it matters: Ema's claim of 80% gross margins on AI-driven enterprise work — paired with 50x revenue growth and a 180% net dollar retention rate — challenges the assumption that automating business processes is a margin-destroying services business. For enterprise software vendors and IT services firms named as customers (PwC, Wipro, NTT DATA, KPMG), Chatterjee's framing that SaaS apps are becoming "like a database" and that human-forward services models may not survive signals a direct threat to their traditional revenue bases.
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