Ema Secures $77M to Deploy AI Agents That Automate Enterprise HR, IT, and Finance Operations

Ema Raises $77 Million to Scale AI Agents Across Enterprises

Agentic AI startup Ema has secured $77 million in Series B funding led by Bengaluru-based venture firm Creaegis, with existing investors Accel, Section 32, and Prosus increasing their stakes1

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. The round brings Ema's total funding to $140 million and more than quadruples its valuation from its $50 million Series A round in 20254

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. The financing consisted entirely of primary equity, with no debt or secondary transactions1

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Founded in 2023 by former Coinbase chief product officer Surojit Chatterjee and ex-Okta executive Souvik Sen, Ema builds what it calls universal AI employees—systems that coordinate multiple AI agents to automate corporate processes across HR, IT, and finance1

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. The Mountain View-headquartered startup has grown to nearly 200 employees with offices in Bengaluru, London, and Vancouver1

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How AI Agents Are Replacing Traditional Enterprise Software

Unlike conventional generative AI chatbots that answer questions, Ema's AI agents take actions and execute complex tasks within enterprise software systems2

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. These AI employees across enterprise carry out multi-step business workflows across a company's existing applications rather than handling single tasks1

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. The platform connects with more than 250 business applications and systems of record, allowing the agents to plan, execute, check their own work, and route sensitive decisions to human employees for approval4

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Chatterjee sees this model as AI starts eating into enterprise software and services. Ema first wraps around an enterprise's existing applications before customers can reduce their dependence on some products and, in certain cases, replace them altogether1

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. "Many of our customers are already on the way to replace large SaaS applications completely, removing dependency on them, because they are mostly becoming like a database," Chatterjee explained1

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Enterprise AI Adoption Moves Beyond Pilot Stage

Ema has more than 50 active enterprise deals and over 1 million active enterprise users, having handled more than 5 million actions and queries1

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. Its customers include NTT DATA, Hitachi, ADP, PwC, Google, KPMG, Wipro, and Microsoft1

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. Over the past two years, Ema's revenue has grown 50-fold, while revenue bookings have surpassed $150 million1

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The startup's net dollar retention rate stands at around 180%, indicating existing customers are spending substantially more with Ema over time1

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. More than 90% of Ema's customers have expanded beyond their initial use case, with some deploying the technology across dozens of workflows1

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"Our customers are not running experiments; they are running their HR, IT and finance operations on AI Employees at a scale of millions of interactions a year," Chatterjee stated2

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. "This round lets us bring that to many more enterprises still stuck in the pilot stage."5

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Real-World Impact: Wipro and Hitachi Deployments

Wipro has deployed an Ema-powered AI assistant for more than 240,000 employees spread across 65 countries2

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. Those AI assistants handle around 2.9 million queries per year across approximately 100 automated workflows, leading to a 50% reduction in IT support tickets2

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Hitachi moved from concept to full production in less than four weeks, integrating Ema's AI employees with more than 20 enterprise systems2

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. Support ticket volumes dropped 30%, while employees increased their efficiency by 70%2

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. Ema's agents now handle more than 1 million IT service management tickets annually, as well as 1 million calls across 15 languages5

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AI-Driven Automation Disrupts Services Business Model

Ema is looking beyond software itself to automate enterprise workflows that companies have traditionally paid IT services firms to perform1

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. "A lot of the services companies are working with us," Chatterjee said. "They are also dramatically changing or disrupting their own business models because they understand the human-forward model may not be the best model going forward."1

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Despite taking on work traditionally handled by software and services providers, Ema has maintained gross margins of close to 80%1

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. The startup requires less human support as its AI systems learn from deployments, helping improve margins over time1

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. Ema does not charge customers based on software seats or AI tokens consumed. Instead, its pricing is tied to task-based pricing for completion of tasks and business outcomes1

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Competing With Frontier AI Labs

Major AI companies like Anthropic and OpenAI have pushed deeper into the enterprise market where Ema operates1

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. Anthropic has expanded efforts to bring Claude into companies' core operations, including financial and legal work, while OpenAI has established teams of forward-deployed engineers who work alongside customers to put AI into production1

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Chatterjee does not see the frontier AI labs as direct competitors. Ema's software can draw on more than 150 models, including frontier and open-source models, while the startup focuses on domain knowledge, integrations, and orchestration needed to automate business processes end-to-end1

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. "Progress in frontier models is actually very beneficial to us," Chatterjee stated1

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What's Next: Global Expansion and Go-to-Market Push

Much of Ema's new capital will go toward expanding its go-to-market operations, particularly sales and marketing, after spending its first years largely building the product1

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. The startup plans to scale into new geographies, including Asia Pacific and Europe, Middle East and Africa4

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. The company will also hire more executive leaders and continue developing its AI employees to enhance their capabilities2

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Prakash Parthasarathy, managing partner and chief investment officer at Creaegis, said Ema is one of only a handful of agentic AI companies that can deliver at enterprise scale2

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. "Ema stands apart, and its platform already supports millions of employee interactions at some of the world's largest organizations," he said2

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According to PYMNTS Intelligence, only 20% of enterprise AI deployments have reached the embedded stage, where AI is a core part of the workflow5

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. Among enterprises with three or more embedded functions, 93% say AI is already delivering a return5

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. "Enterprises do not need more software. They need outcomes," Chatterjee emphasized4

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