Prentis, a new AI research lab focused on computer-use models, is in talks to raise $100 million at a $1 billion valuation, according to two people familiar with the discussions. Launched in April, Prentis is training models to learn how office workers navigate routine workflows across documents and systems, with the goal of building AI agents that can control computers to automate those tasks. The startup aims to develop agents tailored to these customers’ needs, such as handling insurance claims and automating customs duty refund exceptions without requiring human intervention to hunt down paperwork.
Prentis has already signed contracts worth up to $50 million with several customers, including healthcare management service organizations, a manufacturer, and goods and clothing manufacturers, according to the two people. This echoes investor materials obtained by TechCrunch that predict an estimated $75 million annualized run rate by the third quarter of this year. (Prentis’ pitch deck notes those figures reflect estimated annualized value based on a contracted fee equal to 20% of savings realized, not recognized revenue, and are 'performance-dependent and subject to final execution.')
By its own account, Prentis says its Hive-32B model outperforms rivals, including OpenAI’s GPT-5.4 and Anthropic’s Claude Opus 4.6, on two computer-use benchmarks: WindowsAgentArena, which measures end-to-end task completion on real Windows applications, and ScreenSpot-v2, which tests a model’s ability to locate the right on-screen control. In its pitch deck, the company argues its edge comes from running a much smaller, cheaper model. It claims roughly 10 times lower cost per task than frontier APIs, saying it’s more economical to deploy across everyday workflows. TechCrunch hasn’t independently verified the company’s benchmark results.
Source: techcrunch
