Ema Raises $77 Million in Funding

September 24, 2026 – Enterprise adoption of artificial intelligence is moving beyond experimentation as companies look for tools that can deliver measurable outcomes across core business functions.

As organizations seek to automate more complex workflows in areas such as HR, IT, and finance, investors are increasingly backing platforms designed to operate at enterprise scale rather than remain stuck in pilot programs. That momentum is fueling new investment in agentic AI companies such as Ema, which has raised $77 million in Series B funding. This was led by Creaegis, with Accel, S32, and Prosus all increasing their existing investments in the company. The financing brings Ema’s total funding to $140 million and more than quadruples its valuation from the previous round.

“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 and very few agentic AI companies have achieved this,” said Surojit Chatterjee, Ema’s CEO and founder. “Enterprises do not need more software. They need outcomes. Our latest funding round will help us drive agentic business transformation at enterprises still stuck in the pilot purgatory. We will also use our new funds to scale our go-to-market organization and expand to new geographies, including APAC and EMEA.”

Scalable Product Platform

“Many agentic AI companies have compelling demos, but few have proven they can deliver in production at enterprise scale,” said Prakash Parthasarathy, managing partner and chief investment officer at Creaegis. “Ema stands apart. Its platform already supports millions of employee interactions at some of the world’s largest organizations, delivering measurable outcomes with the governance enterprises require. Just as compelling is the strength of the underlying business: Ema has built a scalable product platform with exceptional economics, not a services model dependent on bespoke implementations.”

A lot of enterprise AI today is really a services business wearing a software label — every deployment has its own bespoke project, with every customer needing an army of consultants to go live, Mr. Chatterjee explained. “But Ema’s product-led model works differently: enterprises deploy and expand AI Employees without a services-heavy implementation behind every step,” he said. “Start in one function, and expand across HR, IT, and Finance on the same platform, with one unified AI Employee experience underneath all of it.”

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Ema’s agentic harness allows users to automate workflows conversationally by leveraging deep domain expertise built across multiple deployments. Ema automatically builds a context graph about an organizations’ processes and every successive deployment makes it smarter about your organization’s ways of working. It also nullifies model risk by combining the output of 100+ LLMs, optimized for the most common enterprise usecases, which delivers higher accuracy and lower costs than using single models like GPT for all enterprise work. This is what makes AI deployments economically rewarding at scale.

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Furthermore, Ema is designed to be enterprise-grade from the first day of use, complying with leading security and governance protocols to keep sensitive enterprise data safe.

Serving Clients

“Our platform has helped us deliver agentic business transformation at several Fortune 500 enterprises, with revenue growing 50x over the past 24 months,” Mr. Chatterjee said. “Our time-to-value (<two months) and industry-leading SLA delivery (>95 percent accuracy at scale) has helped us embed ourselves deeply into customers’ workflows. Today, on average, each customer spends two times their initial spend on Ema within 12 months of the contract being signed. As we expand, we will continue to invest in making the platform deliver value from day one.”

“Most tools were built to answer questions or draft a first pass, then hand the rest back to a person and a ticket queue,” said Mr. Chatterjee. “But the work enterprises are trying to eliminate isn’t the thinking, it’s the coordination: chasing an approval, updating five systems by hand, re-explaining the same request to a different queue.”

“Ema was built to handle that coordination entirely,” he explained. “That is why it holds up once real volume hits, instead of degrading the way many pilots do.”

“We see this funding round as another fillip to our founding mission: to transform world GDP with agentic AI employees,” said Mr. Chatterjee. “We can’t wait to help more enterprises get to where our customers are. Here’s to the next chapter.”

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Contributed by Scott A. Scanlon, Editor-in-Chief and Dale M. Zupsansky, Executive Editor  – Hunt Scanlon Media