Oumi PBC, a startup promoting an open artificial intelligence platform built in concert with researchers from some of the world’s most prominent universities, today introduced a platform designed to automate the development of custom AI models, positioning it as a way for enterprises to move beyond reliance on large, general-purpose offerings.

The announcement builds on what the company says is the momentum its earlier open-source project has built, including nearly 9,000 positive ratings on GitHub and adoption by dozens of research institutions. The new platform targets a broader audience, particularly enterprise teams that lack the time or expertise to build models from scratch.

The company’s pitch centers on automating what has traditionally been a complex, multistep process. Enterprises increasingly want to move away from large, closed models toward “small language models,” specialized alternatives tailored to their specific needs, said Chief Executive Manos Koukoumidis (pictured).

“We’ve seen a wave of enterprises that started with large, off-the-shelf models but now want to move to open specialized SLMs,” which offer benefits such as greater relevance to specific projects, lower cost and lower latency, Koukoumidis said. That transition has been slowed by the difficulty of building custom models, a process that can take months, he said.

End-to-end automation

Oumi’s platform is designed to address that barrier by automating the end-to-end workflow, including data generation, evaluation, training and iteration, which are “all the steps that an AI engineer takes to develop a custom model,” Koukoumidis said.

The company claims the system can build custom AI models up to 100 times faster than conventional processes, reducing weeks or months of human effort to hours or minutes.

Oumi said it can also reduce the technical barriers to model generation by allowing users to define a task in natural language. “All you need to do is say, ‘I want to build a model,’ and then you kick it off,” Koukoumidis said.

The platform then automates key tasks such as defining evaluation metrics, generating synthetic data and refining models based on performance gaps. “It analyzes the results for you, automatically synthesizes data, fine-tunes the model and keeps iterating,” he said. “It automates all the steps of an engineer.”

The system supports a wide range of open models. Pricing is based on usage, including compute and tokens for training and inference. Oumi said the cost is offset by reduced engineering effort. “The amount of human effort that it saves is much higher than the bill you’re going to get to train,” Koukoumidis said.

Oumi, which operates as a public benefit corporation, frames the platform as part of a broader effort to decentralize AI development. Koukoumidis said the company’s goal is to “democratize the use of AI and put the future of AI in the hands of enterprises.”

Photo: Oumi