AIData.Broker

For a business system (Slack, Microsoft 365, Google Workspace, Salesforce, HubSpot, Zendesk, Zoom, GitHub, Notion and more): whether the holder can export its data, what the vendor's API terms say about training AI on data pulled through them, our reading of the content's rights risk, and the clauses word for word. Research from public sources, not legal advice. Without `system`, lists the systems on file.

One company of the AI data market (Scale AI, Mercor, Surge AI, Appen, Snorkel AI and the rest of the vendor register): its revenue over time read as twelve months, its growth over about a year, and its ranked competitors (the companies that sell at least two of the same things). Or two companies side by side: which ranks higher and on what, their revenue, valuation and funding, and what each sells. Every figure with the publication that stated it.

Organisations with a public way to sell them data, with their own published terms: what they want, what they pay, when they pay, who removes personal data, eligibility, and what they pay an introducer. Largest published figure first.

Every lot publicly on offer in the catalogues the lot index reads each day (companies' records, codebases, footage, speech, environments), in one vocabulary: kind, industry, years of history, systems, size, what its catalogue says about the rights and whether it is ready, each linked to its catalogue's own page. We have not checked any catalogue's claims. No holder is named. Longest history first.

Vendors that sell training data, RL environments, evaluations, expert work or annotation to AI developers, each with what it says it sells and where its data comes from in its own words, and whether it says it pays holders for data. A to Z, not ranked.

Median, middle half and range per comparable unit (per hour of video or audio, per image, per task, per company, per title, and more) for each kind of AI training data and each side of the market, computed from published prices. Without `kind`, returns every rate the evidence supports a median for.

Every table behind these tools as a CSV and JSON download (our compilation of the tables under CC BY 4.0; quotes keep their sources' terms, and article text is not covered), with row counts, review dates and the permanent copies with their DOIs.

The companies that sell AI developers training data, expert work, labeling, RL environments or evaluations, ranked by twelve-month revenue, then newest valuation, then money raised, each figure with the publication that stated it. One list per kind of work (AI data labs, RL environment companies, data labeling, evaluations, training data providers, and coding, robotics, medical, speech, video, finance, legal, red teaming, multilingual, synthetic and computer-use data), or every company.

Lawsuits, rulings, settlements and regulatory actions over data used to train AI, with parties, claim, amounts, outcome, status and the source. Newest first.

Licences of data to AI companies disclosed since July 2023: licensor, licensee, content, use (training or display), term, value where disclosed, with a verbatim quote and the source. Newest first.

The individual price observations behind the market rates: what a lab, vendor, marketplace or court said data was paid, offered, listed or sold for, with the figure as published, the figure per unit, the date, the source's own words and a link. Newest first.

What published prices imply for a holding of data: a low-to-high range in US dollars with the arithmetic behind it. Call it first with only `kind` to get the questions and their answer ids, ask the holder, then call again with `answers`. Questions not answered are taken at their defaults and marked as assumed. An indication, not an offer.