Best data for AI: the data models can't learn from the web
Best data for AI is rights-cleared, private data that shows how real work gets done — company operating records, expert demonstrations and code with its history. Labs pay for it because public web text is running out and does not show decisions and outcomes. Published ranges are each buyer's own figures, checked on the date shown. They are not an offer, quote, valuation, or guarantee of payment. AIData.Broker's compilation of public figures puts the median published offer at about $280,000 per company and the median public sale at about $31,600 — most companies should expect an actual offer, if any, only after a buyer reviews a metadata-only manifest, and it may be below published ranges or none at all.
Best data for AI, by what a model needs to learn
The category is clearer when it is ranked by use case instead of by vendor. Each of these is a real buying category with published demand behind it — the full breakdown, with what “good” looks like in each, is on the best data for AI by use case page.
| Use case | Best data for it | Why it is scarce |
|---|---|---|
| AI agents that do office work | Operating records: email, chat, CRM, tickets, project files | Private, rights-held, never published |
| Expert reasoning | Expert demonstrations, preference pairs, evaluation sets | Requires senior practitioners and review |
| Coding models | Code with tickets, reviews, tests and outcomes | Public code rarely includes the reasoning trail |
| Industry workflows | Case files, drawings, workpapers, SOPs by vertical | Held inside firms under client obligations |
How labs actually buy it
- Specification — the lab defines the task, industry and record types it needs.
- Manifest, not files — the owner lists systems, years and rough counts. Nothing raw is shared to get an initial view.
- Redacted sample under NDA — the buyer checks the record shows reasoning and outcomes, and that rights are clean.
- Licence, not a sale — limited use, a set term, exclusivity negotiated (it changes price materially). The owner keeps ownership.
- De-identified delivery — personal data removed before transfer; payment terms are in the signed licence.
The step-by-step version, including the routes compared (direct to a lab, via a supplier, via a broker, via a marketplace), is the sourcing guide.
Frequently asked questions
What is the best data for AI training?
The best data for AI training is data a model cannot learn from the public web: rights-cleared records of how real work gets done — operating records, expert demonstrations with the reasoning shown, and code with its review history. Quality is judged on provenance, rights, completeness and whether the record shows a decision and its outcome, not on raw volume.
Who buys the best data for AI?
AI labs and the training-data companies that supply them buy data. Buyers that publish programmes include micro1, Mercor, Scale AI and Handshake AI. Published ranges run from $20,000 to over $3 million per company (buyer pages checked November 2026), and most completed sales are far below the ceilings.
How does a lab source company operating data?
A lab or its supplier defines a specification, reviews a metadata-only manifest (systems, years, record counts — no raw records), sees a redacted sample under NDA, then signs a licence directly with the company that owns the data. De-identification happens before transfer. That route is described in full in the sourcing guide on this site.
Is this site a data lab?
No. Best Data for AI is a sourcing guide published by BestDataForAI.com, which also operates a data-licensing introduction service. BestDataForAI.com helps U.S. companies with 20+ employees license their operating records — email, chat, CRM and project data — to AI labs and training-data buyers. Owners keep ownership of their data; valuation starts with a metadata-only manifest, and no raw data is shared to get an estimate.
What does it cost a lab to start a sourcing conversation?
Nothing on this site. Labs use the request-supply form to describe a specification; any commercial terms are agreed in writing with the data owner and any supplier involved before anything is delivered.
Building or buying for an AI team?
Describe the specification — industry, record types, volume, exclusivity. We reply with what supply actually exists against it, not a catalogue of promises.
Sources — checked November 2026
- micro1 data partnerships page — published tiers $100K–$500K / $500K–$3M / $3M+, checked November 2026 (micro1.ai).
- Mercor referral listings — $20,000–$1.5M per company by industry, checked November 2026 (mercor.com).
- AIData.Broker public price compilation — median published offer ≈$280,000; median public sale ≈$31,600, checked November 2026.
- Spirit Airlines archive auction — Google $10M successful bid, Mercor $7.5M backup, August 2026 court filings, reported by iTnews / MIT Technology Review.
Cite this entry: Best Data for AI. “Best Data for AI — What It Is, Who Sells It, How Labs Buy It (2026).” Content reviewed 10 November 2026. Figures on this page are published buyer ranges with sources and check dates shown — they are not offers.