Ema has raised $77 million in Series B funding as the enterprise AI startup expands its push to automate work traditionally handled by software applications and IT services companies.
The round, announced September 23, was led by Creaegis, with existing investors Accel, Section 32 and Prosus increasing their investments. The financing brings Ema’s total funding to $140 million and more than quadruples its valuation from its previous financing in 2024, although the company has not disclosed its latest valuation.
But the funding is only part of the story.
Ema is betting that businesses may eventually buy fewer traditional software tools and instead use AI agents to complete work across the applications they already have.
What Ema Is Building
Founded in 2023 by former Google and Coinbase executive Surojit Chatterjee and former Okta executive Souvik Sen, Ema develops what it calls “AI employees.”
These systems coordinate multiple AI agents to perform multi-step processes across HR, IT and finance rather than simply answering questions or generating documents.
The distinction is important.
Traditional enterprise software typically gives employees tools for completing specific tasks. An employee might use one system to submit an IT request, another to manage HR information and another to handle financial processes.
Ema’s approach is to sit across those existing systems and coordinate the work.
Its platform can connect to enterprise applications, understand business processes and execute workflows involving multiple steps. Ema says its technology can use more than 100 large language models and open-source models rather than depending on a single underlying model.
That puts Ema in a different position from companies building foundation models. Its focus is the layer between AI models and the actual business processes companies need to automate.
Why the $77 Million Matters
The new funding comes as AI companies increasingly compete for enterprise technology budgets.
For years, businesses have purchased software through subscription models, often paying according to the number of employees or seats using an application. IT services firms then provide implementation, integration and ongoing support.
Ema’s model challenges parts of that structure.
CEO Surojit Chatterjee told TechCrunch that Ema initially works alongside customers’ existing software but can eventually reduce their dependence on some applications. He argued that some large SaaS products could become primarily systems for storing data while AI agents handle the work performed on top of them. That is Ema’s thesis, not an independently established industry-wide outcome.
The company’s pricing also reflects that philosophy.
Rather than charging customers according to software seats or AI-token consumption, Chatterjee told TechCrunch that Ema prices its service around completed tasks and business outcomes.
If that approach becomes more common, it could represent a meaningful change in how enterprise software is purchased.
Ema Says Enterprise Adoption Is Growing
Ema says it now has more than 50 active enterprise deals and more than 1 million active enterprise users. The company says its systems have processed more than 5 million actions and queries. Customers named by Ema and reported by TechCrunch include NTT DATA, Hitachi, ADP, PwC, Google, KPMG, Wipro and Microsoft.
The company also reports that revenue has grown 50-fold over the past two years and that revenue bookings have exceeded $150 million.
That bookings figure should not be confused with annual recurring revenue. Ema told TechCrunch that the figure includes the total value of multiyear contracts, including two- and three-year agreements. The company has not disclosed its current annualized revenue run rate.
Ema says more than 90% of its customers have expanded beyond their initial use case, with some deploying its technology across dozens of workflows. It also reports a net dollar retention rate of approximately 180%.
Those figures come from Ema and statements made by its CEO, rather than audited public-company disclosures.
AI Agents Could Change the SaaS Relationship
The most significant part of Ema’s strategy may be its argument that AI agents can become an orchestration layer across existing enterprise software.
Instead of asking an employee to navigate several systems manually, an AI agent could potentially receive the desired outcome and coordinate the underlying actions.
For example, an employee could request a business process involving an HR system, an identity-management platform and an internal approval workflow. An agent could coordinate those systems while escalating decisions that require human approval.
That model is closely related to concepts such as AI workflows and AI automation — areas increasingly relevant as companies move from AI experimentation toward operational deployment.
The opportunity is not limited to software.
Chatterjee also told TechCrunch that AI could reduce some of the implementation, integration and consulting work traditionally performed by IT services companies. Ema says it maintains gross margins close to 80%, although that figure is a company-reported metric rather than independently verified financial guidance.
Ema Is Betting on Production, Not Just AI Pilots
Ema’s September funding announcement repeatedly emphasizes a distinction between AI demonstrations and AI systems operating in production.
The company says an AI employee deployed by Wipro supports more than 240,000 employees across 65 countries, automates more than 100 workflows and handles approximately 2.9 million employee queries annually. Ema also says response times have fallen from days to seconds in that deployment.
Those are Ema’s reported customer results.
The broader enterprise AI market is still developing, but the shift from experimental chatbots toward systems capable of executing multi-step workflows is becoming increasingly important. QueryFeedz’s existing coverage of how AI is changing the way companies work provides useful context for that transition.
What Happens Next?
Ema plans to use the new capital primarily to expand its go-to-market organization and continue developing its enterprise AI platform. The company also plans to expand into additional international markets, including regions across Asia-Pacific, South America and the Middle East.
The bigger test will be whether Ema’s model can scale beyond individual automation projects and become a meaningful alternative layer for enterprise work.
For SaaS companies, the development raises a different question: if AI agents increasingly become the interface employees use to interact with software, how much value will businesses continue to place on traditional application interfaces and per-seat subscriptions?
Ema’s $77 million funding round does not answer that question.
It does, however, show that investors are putting significant capital behind the idea that enterprise AI may eventually compete not just with individual software features, but with the way businesses organize and purchase software itself.
