Prentis, a new artificial intelligence research lab focused on computer use models, is in talks to raise $100 million at a $1 billion valuation, according to people familiar with the discussions. The startup, co-founded by serial entrepreneur Ritankar Das and tech heavyweights Reid Hoffman and Mark Pincus, aims to build AI agents that can autonomously control computers to automate routine office workflows. Launched in April, Prentis has already signed contracts worth up to $50 million with several customers and claims its proprietary model outperforms offerings from OpenAI and Anthropic on key benchmarks.
Prentis seeks $100 million at $1 billion valuation: What it means
Prentis is training models that learn how office workers navigate routine workflows across documents and systems. The goal is to develop AI agents that can control computers to automate those tasks, such as handling insurance claims or automating customs duty refund exceptions without requiring a human to hunt down paperwork. The company argues that automating everyday office tasks will soon outpace coding as AI’s biggest use case, though it faces a crowded market that includes Anthropic, OpenAI, and Mira Murati’s Thinking Machines Lab.
What is Prentis and what does it do?
Prentis is an AI research lab that builds models for computer use — a category of AI that enables software to interact with graphical user interfaces, click buttons, fill forms, and navigate applications just as a human would. The startup’s Hive-32B model is designed to run on a smaller, cheaper infrastructure than competitors, claiming roughly 10 times lower cost per task than frontier APIs. This economic advantage is central to Prentis’s pitch: making AI agents practical for everyday office workflows across industries like healthcare, manufacturing, and logistics.
The founding team behind Prentis
Ritankar Das, CEO of Prentis, is also the founder of Titan, a holding company that builds and operates AI companies. 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 had been a Gates Cambridge Scholar. Das has described Titan as an intentional throwback to an old-fashioned holding-company model like Berkshire Hathaway, one funded by its own exits rather than outside limited partners.
Reid Hoffman, the LinkedIn co-founder and Greylock partner, said last month that he was stepping down from Microsoft’s board after nearly a decade to go “founder mode” on Manas AI, an AI drug-discovery startup. Hoffman was an early OpenAI investor and co-founded Inflection AI with Mustafa Suleyman before Microsoft absorbed most of that team in 2024. Mark Pincus, the Zynga founder, runs the investment firm Reinvent Capital with Hoffman as a senior adviser and published a memoir, “Life at the Speed of Play,” last month. Prentis is a side project of sorts for both Hoffman and Pincus.
How does Prentis’s Hive-32B model compare to OpenAI’s GPT-5.4 and Anthropic’s Claude Opus 4.6?
Prentis claims its Hive-32B model outperforms 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. The company argues its edge comes from running a much smaller, cheaper model, resulting in roughly 10 times lower cost per task than frontier APIs. These claims have not been independently verified by TechCrunch.
Early customer traction and revenue model
Prentis has already signed contracts worth up to $50 million with several customers, including a healthcare management service organization, a manufacturer, and goods and clothing manufacturers. Investor materials obtained by TechCrunch predict an estimated $75 million annualized run rate by the third quarter of this year. However, the pitch deck notes that 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.” The startup is essentially betting on a revenue model tied to cost savings delivered to clients, rather than subscription fees or per-seat licensing.
The crowded landscape of AI agents for computer use
Anthropic, OpenAI, and Mira Murati’s Thinking Machines Lab are also working on developing AI agents for computer use. Anthropic has been particularly active in the category, acquiring the Seattle computer-use startup Vercept earlier this year, folding in its founders and shutting down its product. Prentis will need to differentiate itself not only on model performance and cost but also on the ability to secure enterprise contracts and build trust with customers who are cautious about handing over control of their workflows to AI agents. The startup has already hired more than 25 employees, including researchers who previously worked at OpenAI, Google DeepMind, Meta, Tencent, and Alibaba, giving it a talent pool that rivals larger competitors.
Titan: the holding company behind Prentis
Other businesses launched and operated by Titan include AI-powered virtual care provider Tala Health, which raised a $100 million seed round last year, and Forta Health, an autism care startup that raised $55 million led by Insight Partners in 2024. Titan-founded disease prediction company Dascena was acquired by CirrusDx in 2022. This pattern of building and scaling AI companies across different verticals — healthcare, logistics, and now enterprise automation — suggests that Das and his team are pursuing a portfolio strategy similar to a venture builder, but with a holding-company structure that allows them to retain long-term ownership and reinvest profits from exits.
Prentis’s valuation of $1 billion, even before closing the $100 million raise, reflects investor appetite for AI agents that can deliver tangible cost savings to enterprises. The startup’s focus on office automation, rather than coding or creative tasks, positions it in a market that could be worth hundreds of billions of dollars if the technology proves reliable. But the competitive landscape is intensifying, and questions remain about how quickly enterprises will adopt computer-use agents at scale. Prentis’s ability to convert its early contracts into recurring revenue, validate its benchmark claims, and fend off well-funded rivals will determine whether the $1 billion valuation becomes a foundation for growth or a peak in a crowded field.
