Prentis, new AI lab co-founded by Reid Hoffman, Mark Pincus in talks to raise $100M
The neolab is betting that automating routine computer tasks will soon outpace coding as AI's biggest use case. Prentis , a new AI research lab focused on computer use models, co-founded by serial entrepreneur Ritankar Das and tech heavyweights Reid Hoffman and Mark Pincus, 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.
Key Takeaways
- Prentis will ostensibly develop agents tailored to these customers' needs, such as handling insurance claims and automating customs duty refund exceptions without needing a human to hunt down paperwork.
The startup has already signed contracts worth up to $50 million with several customers, including healthcare management service organization, a manufacturer, and goods and clothing manufacturers, the two people familiar with the discussions tell TechCrunch.
- ") By its own account, Prentis says its Hive-32B model outperforms rivals, including OpenAI's GPT-5.
- TechCrunch hasn't independently verified the company's benchmark results.
The startup is betting that automating everyday office tasks will soon outpace coding as AI's biggest use case, but it's a crowded market.
- Das, now 31, was UC Berkeley's youngest University Medalist in more than a century , graduating at 18 with a double major in bioengineering and chemical biology before earning a master's in biomedical engineering at Oxford.
He founded Titan in 2014 after dropping out of an AI PhD program at Cambridge, where he'd been a Gates Cambridge Scholar.
- Prentis is a side project of sorts for its two other co-founders.
Stats & Key Facts
- #Prentis , a new AI research lab focused on computer use models, co-founded by serial entrepreneur Ritankar Das and tech heavyweights Reid Hoffman and Mark Pincus, is in talks to raise $100 million at a $1 billion valuation, according to two people familiar with the discussions.
- #The startup has already signed contracts worth up to $50 million with several customers, including healthcare management service organization, a manufacturer, and goods and clothing manufacturers, the two people familiar with the discussions tell TechCrunch.
- #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.
Prentis will ostensibly develop agents tailored to these customers' needs, such as handling insurance claims and automating customs duty refund exceptions without needing a human to hunt down paperwork. The startup has already signed contracts worth up to $50 million with several customers, including healthcare management service organization, a manufacturer, and goods and clothing manufacturers, the two people familiar with the discussions tell TechCrunch. 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. In fact, it claims roughly 10 times lower cost per task than frontier APIs, saying it's more economical to deploy across everyday workflows.
For more details please read the original article at TechCrunch AI.
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