Three-month-old AI startup Prentis, backed by Reid Hoffman, eyes $1 billion valuation with a bet on automating office work

A three-month-old AI startup wants to make repetitive office work something humans no longer have to do and investors could value the bet at $1 billion. Prentis, founded by serial entrepreneur Ritankar Das alongside LinkedIn co-founder Reid Hoffman and Zynga founder Mark Pincus, is in talks to raise $100 million at a $1 billion valuation, according to TechCrunch. Launched in April, Prentis is building “computer-use” AI models. Instead of simply answering questions like a chatbot, these models are designed to understand what is happening on a computer screen and operate software directly. The goal is ambitious: teach AI how people actually work, then let agents perform those workflows themselves.

Prentis wants AI to learn your office work

Many workplace processes are never properly documented. Employees simply learn which file to open, which button to click and what to do when something goes wrong. Prentis wants its models to learn these patterns by observing and interacting with real workflows. That could eventually allow customised AI agents to handle tasks such as insurance claims or customs duty refund exceptions without employees manually searching through documents and different systems. The startup has reportedly already signed contracts worth up to $50 million with customers across healthcare and manufacturing.

Prentis claims its smaller AI can beat bigger models

At the centre of the company’s pitch is Hive-32B, its computer-use model. Prentis claims Hive-32B outperforms OpenAI’s GPT-5.4 and Anthropic’s Claude Opus 4.6 on two computer-use benchmarks, WindowsAgentArena and ScreenSpot-v2. More importantly for businesses, Prentis reportedly claims its model can perform tasks at roughly one-tenth the cost of frontier AI APIs. However, these performance claims have not been independently verified.

Why office work could become AI's next battleground

Prentis is betting that computer automation could eventually become a bigger AI use case than coding.

But it is entering an increasingly competitive market.

OpenAI and Anthropic are also developing AI systems capable of interacting with computers. The attraction is clear: an AI agent that can actually operate workplace software could do far more than simply draft an email or summarise a document. Prentis argues that its advantage comes from training AI on something frontier models may lack exposure to the undocumented steps, exceptions and hand-offs involved in real work. Its small team already includes researchers with experience at OpenAI, Google DeepMind, Meta, Tencent and Alibaba. For Prentis, the bigger bet is that the next stage of the AI race will not simply be about building smarter chatbots. It will be about building AI that can sit at a computer and actually get the work done.