The complete, unabridged record of real human work.
Full screen recordings of professionals doing their actual jobs, plus the metadata around them. Nothing synthetic, nothing summarized, and nothing edited out except PII.
The next generation of models, especially agents that are supposed to do work rather than talk about it, needs data about how work actually gets done. That data is getting hard to find.
Most of what could be scraped already has been, and a good share of what remains is tied up in court.
Models trained on model output inherit its gaps and blind spots. Synthetic data can rehearse what a model already knows. It can't add anything new.
Docs, wikis, and Q&A sites record conclusions. The process that produced them, the part worth learning from, never gets written down.
The work itself has never been on the web. Every step, correction, dead end, and judgment call an expert makes on the way to a finished product happens on a screen, in real time, and then it disappears. We captured it: full screen recordings of professionals doing real work, with the metadata to go with them.
Models trained on summaries learn summaries.
Ours is the full record.
End-to-end workflow data for training models that operate tools, sustain long tasks, and recover from errors the way experts do.
How specific kinds of knowledge work actually get done, for models that need to perform a profession rather than paraphrase its textbook.
Real human workflows as the benchmark for whether an agent actually does the job, not whether it sounds like it does.
The corpus was captured in the ordinary course of work, with consent and a clear chain of custody. Licensing terms are explicit and auditable. No scraping ambiguity, no downstream surprises. Provenance isn't a feature here. It's the product.
Unabridged is quiet by design. Corpus scope, composition, and terms are shared under NDA. If data quality is the bottleneck on your roadmap, we should talk.