Ema, a startup that uses teams of AI agents to automate enterprise processes across HR, IT, and finance, has raised $77 million in a new funding round as it aims to take on much of the work traditionally handled by enterprise software and IT services.
The Series B round was led by Bangalore-based venture firm Craeegis, with additional funding from existing investors Accel, Section 32, and Prosus. The latest funding brings the startup’s total funding to $140 million, more than quadrupling its valuation since its previous funding round in 2024 (Ema declined to disclose its latest valuation). The round was comprised entirely of primary equity, with no debt or secondary deals, the startup confirmed to TechCrunch.
The funding comes as AI competes for money that companies traditionally spend on enterprise software and IT services. Startups, big AI labs, and established software companies are now scrambling to capture that spending.
Founded in 2023 by former Google and Coinbase executive Surojit Chatterjee and former Okta executive Subik Sen, Ema aims to expand its position in the market. The startup is introducing its technology, which it calls “AI Employee,” a system that coordinates multiple AI agents. They help you run multi-step business processes across your company’s existing applications, rather than handling one task at a time.
Chatterjee sees this model ultimately reducing companies’ dependence on traditional software products, including products sold as software-as-a-service (SaaS). He said Ema can first “wrap” a company’s existing applications, then reduce the customer’s dependence on some of those products, and in some cases replace them completely.
“Many of our customers are already looking to completely replace (large SaaS applications) and eliminate dependencies because they are becoming almost database-like,” Chatterjee said.
Benefit from AI Lab Acceleration
In recent months, major AI companies have also moved deeper into the enterprise market where Ema operates. Anthropic is expanding its efforts to include Mr. Claude in the company’s core operations, including finance and legal operations. Similarly, OpenAI has established a team of forward deployment engineers who work with customers to bring AI into production.
However, Chatterjee does not consider Frontier AI Institute to be a direct competitor. He told TechCrunch that while Ema’s software has over 150 models available, including frontier and open source models, the startup is focused on the domain knowledge, integration, and orchestration needed to automate business processes end-to-end.
“Advances in the frontier model are actually very beneficial to us,” Chatterjee said.
Ema’s approach is already attracting attention. The startup has over 50 active business deals and over 1 million active business users, and has processed over 5 million actions and queries. Customers include NTT Data, Hitachi, ADP, PwC, Google, KPMG, Wipro, and Microsoft.
Over the past two years, Ema said revenue has increased 50 times with revenue bookings exceeding $150 million. Chatterjee said the booking value does not represent annual recurring revenue, but instead includes the total value of multi-year contracts, including two-year and three-year contracts. However, he declined to reveal the startup’s current annual revenue run rate.
Chatterjee told TechCrunch that more than 90% of Ema’s customers have expanded beyond their initial use cases, with some deploying the technology across dozens of workflows. He said the startup’s net dollar retention rate is around 180%, meaning existing customers are spending substantially more money with Ema over time.
Ema is also looking beyond the software itself. Chatterjee said AI can take over some of the implementation, integration and consulting work that companies traditionally pay IT services companies to do for enterprise software.
“Many service companies are working with us,” Chatterjee said. “They also understand that the human-first model may not be the best model going forward, so they are dramatically changing or disrupting their business models.”
Chatterjee said Ema has maintained a gross margin of nearly 80% despite taking on work traditionally handled by software and service providers. He noted that because the company’s AI systems learn from deployments, the startup will require less human support and increase profit margins over time.
Ema also does not charge customers based on the number of software seats or AI tokens consumed. Instead, its pricing is tied to task completion and business outcomes, Chatterjee said.
Much of Ema’s new capital will go toward go-to-market operations, particularly sales and marketing expansion, after spending the first few years primarily building the product, Chatterjee said. Headquartered in Mountain View, the startup has grown to nearly 200 employees and has offices in Bengaluru, London, and Vancouver.
Ema has so far primarily focused on customers in the United States and Europe. But the company is now planning to expand into new markets over the next year, particularly in parts of Asia Pacific, South America and the Middle East.
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