Startups that are shutting down are now selling off their company data, including emails and Slack messages, for as much as hundreds of thousands of dollars to help train AI models.
Forbes reports that companies that specialize in winding down startups are helping founders squeeze out some last-minute cash by monetizing their internal communications.
While large language models were initially trained on public internet data like books, news articles, Wikipedia, and Reddit threads, newer agentic AI models require more complex datasets that reflect how work actually gets done.
That training often happens in so-called “reinforcement learning gyms” or RL gyms. These simulated environments are built using real-world company data and allow AI agents to practice completing workplace tasks like planning a birthday celebration for a coworker. This kind of training data has quickly become very lucrative. The Information reported last year that leaders at Anthropic discussed spending up to $1 billion on RL gyms.
Now, the companies that help startups shut down by handling things like payroll, taxes, and investor settlements are getting in on the action.
For example, SimpleClosure this week introduced a new product called Asset Hub, aimed at helping startups monetize their data.
The platform allows companies to license things like source code as well as workplace data, including documents, workflows, and internal communications such as Slack messages and emails.
According to its website, SimpleClosure helps companies determine what data can be sold, assess its value, and process it to remove personally identifiable information.
SimpleClosure did not immediately respond to a request for comment from Gizmodo.
Forbes reports that over the past year, SimpleClosure has processed nearly 100 of these deals, with payouts ranging from $10,000 to $100,000 per company.
“There’s a feeling of a gold rush from these companies trying to get their hands on real-world data,” SimpleClosure CEO Dori Yona told Forbes.
Still, some privacy advocates are raising concerns about what this means for workers whose data may be included in those datasets.
“I think the privacy issues here are quite substantial,” Center for AI and Digital Policy Founder Marc Rotenberg told the outlet. “Employee privacy remains a key concern, particularly because people have become so dependent on these new internal messaging tools like Slack…It’s not generic data. It’s identifiable people.”
The Center for AI and Digital Policy also recently sent a letter to the Senate Commerce Committee urging the Federal Trade Commission to step up its oversight of AI-driven businesses.
