Oumi Want Every Enterprise to Build Its Own AI Brain

Oumi launched its Compounding AI Factory this month, a platform built to automate the development of specialized enterprise artificial intelligence models. Instead of assembling a team of machine learning engineers to build, evaluate and improve a model by hand, the company argues AI itself can do that work, letting enterprises continuously develop intelligence tailored to their own data and operations.

For Co-Founder and CEO Manos Koukoumidis, the launch points to something bigger than one product. “We’re going to be looking again back in, I don’t know, six months, a year from now, and saying it was obvious that you could use AI to automate AI development,” he told PYMNTS. “It’s a more tedious task. It’s a task that’s more automatable with AI.”

He said that once building custom AI becomes easier, enterprises will start questioning another assumption baked into the generative AI era: that intelligence should be rented from frontier labs in the first place.

The Compounding AI Factory is built to strip out the technical barriers that have historically limited custom AI development. Rather than manually building evaluation datasets and generating training data through repeated cycles, Koukoumidis said enterprises should let AI handle much of that process. Organizations describe the capability they want, and the platform generates data, evaluates performance, trains a specialized model and keeps improving it as it interacts with production.

He compares the shift to what coding assistants have already done for software engineering. “The same way that Claude made the deepest software engineers more efficient but also democratized software development … we’re doing this now for AI development,” he said.

The point isn’t only to make existing machine learning engineers faster. Koukoumidis believes automation lets enterprises without deep machine learning expertise build their own specialized models, cutting both the cost and the complexity of getting there. Customers can build independently or work alongside Oumi engineers first, and tasks that once took weeks of engineering time can now be kicked off with only minutes of user interaction while training runs automatically in the background.

Enterprises Are Beginning to Rethink Renting AI

Making it easier to build custom models also changes the economics of renting versus owning AI. Koukoumidis said many enterprises first adopted frontier models because they offered the fastest path to experimentation. But as AI becomes central to competitive differentiation, he said companies are reconsidering whether relying on third-party providers is still the right long-term strategy. “We can’t be renting our AI,” he said. “We’re seeing a big shift happening in the industry towards this direction where enterprises are exploring other strategies.”

He likens it to earlier waves of enterprise software: companies start with generic tools because they’re easy to deploy, then move toward systems they own once they start caring about performance, economics and control. He said ownershjp also reduces exposure to a vendor’s pricing decisions, roadmap changes and geopolitical risk, while keeping proprietary knowledge inside a company’s own systems rather than exposing it through someone else’s model. “Every company should build, own, compound its own intelligence as its IP,” Koukoumidis said.

The distinction that matters most, in his view, isn’t model size. It’s specialization. “If you’re doing an operation on a human, you don’t use the biggest Swiss Army knife you can find,” he said. “You use a scalpel.” A model built specifically for a bank’s risk analysis or an insurer’s claims processing can outperform a much larger frontier model at a fraction of the cost, because it’s trained on an enterprise’s own proprietary data rather than the broad public web, and it keeps compounding in value the longer it runs in production.

That shift is already underway, according to Koukoumidis. As AI automates the process of building AI, he expects more enterprises to stop treating intelligence as something they consume through an API and start treating it as infrastructure they own outright.

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