The AI labs ran out of internet

Every large language model you have used was trained on roughly the same thing. Wikipedia, news archives, code repositories, books, forums, and as much of the open web as could be scraped before the doors started closing. That material is finite, and most of it has now been used.

What the labs are short of is not more text. It is a record of how work actually gets done.

Consider what is missing from the public internet. How a purchase order moves through four approvals and gets stuck on the third. How a support ticket escalates, and what the engineer tried before it did. How a price was negotiated over eleven emails and a phone call nobody wrote down. How a shipment was rerouted when a supplier went quiet. None of that is published anywhere. It exists only inside the systems of companies that were not thinking about AI when they started collecting it.

That is the gap. And it is why the market for company records has moved in eighteen months from a curiosity to something with prices attached.

What the buyers look like

They are not all AI labs. Four groups are active, and they want different things.

AI platforms want process, sequence and outcome. They are trying to teach a model what competent work looks like, which means they need examples of work rather than descriptions of it.

Data aggregators buy to enrich products they already sell. A firm selling supply chain intelligence needs shipment records. One selling credit signals needs payment behaviour. They are the most frequent buyers because they know exactly what a gap in their coverage costs them.

Investment funds want early indicators. Transaction volumes, subscription churn, hiring, freight movement, all of it read as a signal about a sector weeks before it shows up in a quarterly filing.

Corporates buy for benchmarking, and occasionally to see something about their own market that their own data cannot tell them.

What this means if you run a software business

If your product records activity rather than just storing records, you are producing the thing that is short. Transactions, events, usage, messages, timestamps, sequences. Ten years of it is not old data. It is history, and history is what lets a buyer test whether a signal holds before they pay for it.

Most companies in this position have never been approached, and assume that means there is no demand. It usually means nobody has looked.