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.

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. 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. Anthropic, Open AI, and Mira Murati’s Thinking Machines Lab are also working on developing AI agents for computer use, one of the sources said. Anthropic has also been acquiring talent in the category directly — it bought the Seattle computer-use startup Vercept earlier this year, folding in its founders and shutting down its product.

Prentis didn’t respond to TechCrunch’s request for comment.

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’d been a Gates Cambridge Scholar. Das has described Titan as an intentional throwback to an old-fashioned holding-company model like Berkshire Hathaway, one that’s funded by its own exits rather than outside limited partners.

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.

Prentis is a side project of sorts for its two other co-founders. 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 he’s also backing; he was an early OpenAI investor and co-founded Inflection AI with Mustafa Suleyman before Microsoft absorbed most of that team in 2024.

Pincus, the Zynga founder, now 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 has already hired more than 25 employees, including researchers who previously worked at OpenAI, Google DeepMind, Meta, Tencent, and Alibaba, according to its website.

OpenAI launched its first piece of hardware last week — a fancy little keypad built to pair with ChatGPT. Micro, which was developed in collaboration with specialty keyboard designer Work Louder, is essentially an artisanal workplace novelty that tech-savvy users will love and that may leave everyone else a little puzzled.

OpenAI’s entrance into the hardware market hasn’t arrived without drama. Several weeks ago, Apple sued the AI lab and accused it of trade theft — kicking off what’s certain to be a long-simmering legal battle. Meanwhile, news of another smart home product in development at OpenAI has also raised eyebrows, as the supposed device — which is being built to pair with ChatGPT — was reportedly developed by former Apple engineers.

Until the legal battle works itself out and OpenAI’s broader hardware ambitions materialize, the most the startup has to offer is Micro — a funky little keypad clearly engineered to delight the tech industry’s code monkeys.

OpenAI sent TechCrunch a Micro test unit. The first big thing you notice when initially handling the keypad is that it’s a sturdy little device — enough so that if the AI accessory thing doesn’t end up working out, it could easily double as a paperweight. The other thing you might notice (and I am not the only one to point this out), is that the packaging — an immaculate white box with a sleek, clean aesthetic — is pretty Apple-coded. Make of that what you will.

The keypad’s layout involves six frosted “agent” keys at the top of the pad, which can be customized to carry out specific tasks within ChatGPT or its agentic coding tool Codex. Below them are six command keys, which can be used to control those programs. You can pair your Micro with your computer either through a Bluetooth connection or a USB cable.

Perhaps the most convenient thing Micro offers is a button for voice dictation — meaning you simply tell the app what you want done and it will get busy working on your behalf. Just hold down the dictation button and start talking. When you’re done, tap the “send” button next to it to submit your request.

You can customize your Micro keypad within ChatGPT itself, where a Micro tab allows you to adjust everything from the brightness of the light from the keys to the specific commands and projects you want tied to those keys.

Coders — the device’s actual target audience — haven’t exactly embraced it. Reviews by Redditors have largely negative, with one Reddit user calling it “a prank and not a real product,” and others saying serious coders won’t touch it. A review by the smaller independent outlet Aftermath was even harsher, calling the $230 price tag hard to justify next to cheaper DIY and off-the-shelf alternatives. (The title of that review: “OpenAI’s expensive macropad feels engineered to piss me off specifically.”)

It’s definitely the case that new users may need some time to figure out how Micro works and what to do with it.

Once I figured out how to program the keypad to my liking, I found it was actually pretty fun. You can assign various ChatGPT sessions to specific keys, which then allows you to easily toggle back and forth between all of your various projects. When you combine that with the dictation button, it makes the whole experience considerably more efficient and enjoyable.

But there’s still a learning curve. Micro’s buttons are color-coded. White means an agent is idle, blue means its thinking, green means a task is complete, and red means there’s been an error. You’ll need to memorize that, along with memorizing which specific projects are coded to each key.

The big question is whether the Micro keypad is functionally easier to use than just continuing to work on your laptop. In short: Why would I spend a week learning how to program and operate this thing when I already know how to use my computer’s mouse and keyboard?

Ultimately, your experience with the Micro will depend heavily on how much you use ChatGPT. Since I don’t use AI much day to day, I’m probably not the target audience for it.

That said, if you’re a ChatGPT power user, have $230 to spare, and like vintage-looking hardware with clicky buttons, Micro probably isn’t the worst purchase you could make — it might even brighten your day a little.

SpaceX successfully deployed the first third-generation Starlink satellites on Friday using an upgraded version of its prototype Starship — the 13th test flight of its mega-rocket to date. But the company suffered another failure with its Super Heavy booster during a planned simulated landing in the Gulf of Mexico.

It’s the second time the company has had an issue with the Super Heavy booster on this V3 version of Starship. In May, on the first Starship V3 flight, SpaceX encountered a failure of the Starship’s Super Heavy booster as it separated from the upper stage of the rocket.

The launch came a little more than a week after SpaceX tried to conduct the 13th Starship launch. That attempt had to abort immediately after ignition due to a number of rocket engine failures. SpaceX said it replaced six engines ahead of Friday’s flight to fix the problem.

During Friday’s launch, the booster made it further into its planned flight, but wasn’t able to properly fire up all of the engines required for its simulated landing burn. The booster exploded after a faster-than-expected impact with the water.

This was the first launch of Starship since SpaceX went public in June in the largest IPO in history. In a test of SpaceX’s “fly, fail, fix” approach to Starship development, the company saw its stock decline last week in the day following the launch abort. The dip is part of a larger downward trend since the IPO that has seen the company’s stock drop from a peak of more than $200 per share to $115 at the close of trading on Friday. In after-hours trading, SpaceX shares fell another 2% following the booster failure, before paring some of those losses.

SpaceX appears to have had better luck with the Starship V3 upper stage during Friday’s launch. The upper stage lost a rocket engine during the first V3 launch in May. That didn’t happen this time around, as Starship encountered no issues on its way to deploying the new Starlinks.

The new Starlink satellites are expected to burn up in the atmosphere roughly 20 minutes after deployment, as Starship still isn’t capable of reaching Earth orbit.

This story is developing…