Sell side · Buyer comparison

Best Data Labs & Marketplaces to Sell Your Data To

The labs with real data-acquisition programs, what each one buys, and the terms each publishes — because in this market, who publishes terms and who doesn’t is itself the first finding. Start with the liability checklist on our sell-side hub before approaching any of them.

At a glance

The routes, in order

1. Micro1 — the operational-data program

Micro1’s “Monetize your company’s operational data” program is the reference offer in this market: published scope tiers, a reported $1 billion 12-month buying commitment, and press-documented participation in the Spirit Airlines data auction ($12.5M competing bid, per court reporting). Its CRO told Business Insider the valuable asset is “long-horizon” data showing how work actually gets done. If your records fit, start here: register your company with Micro1.

Disclosure: this is a referral link. Micro1’s referral terms pay on Enterprise Data Partnership deals — if your company registers through this link and enters such a deal, we may earn a referral commission at no cost to you. We route introductions only: eligibility, terms and pricing are Micro1’s, not ours.

Full profile: Micro1.

2. Nyne AI — published terms for US operating companies

Nyne licenses de-identified accounting, CRM and dispatch records from US companies with 20+ W-2 employees and 3+ years of history, pays on delivery and acceptance, and publishes both its value guidance (“commonly $100K or more”) and a price-match on qualifying written offers — which makes it the natural second quote. Profile: Nyne AI.

3. Appen — Enterprise Data program

The incumbent’s sell-side door: Appen states it partners with enterprises to anonymize and license operational data to frontier labs, covers extraction, anonymization and transfer costs, agrees terms in writing before extraction begins, and pays on acceptance. A faster path for companies winding down, per its program description. Profile: Appen.

4. Mercor and Handshake — named in press as document/record buyers

WIRED (November 2026) names Mercor, Micro1 and Handshake as the leaders buying company databases and professional documents; Handshake confirmed it licenses professional documents so labs can test models on real knowledge work. Neither publishes a data-partnership rate card — approach them as negotiated deals, and get competing offers in writing (Nyne’s price-match makes written offers doubly valuable). Profile: Mercor.

5. FileYield — private brokerage

Describe the dataset in plain language, stay private, negotiate directly with buyers. A very new entrant with conflicting public fee statements — read our profile’s considerations before engaging: FileYield.

6. DataVendor (HUD) — code, data, RL environments

The codebase specialist: grading before buyer review, non-exclusive by default, published 20% withdrawal fee. Profile: DataVendor.

7. Troveo and Versos AI — video and media

Troveo aggregates thousands of rights holders and pays royalties per licence; Versos AI prepares premium libraries in place with C2PA provenance. Profiles: Troveo · Versos AI.

8. Defined.ai — dataset marketplace partner program

For finished datasets (speech, text, image, video) rather than raw company records: Defined.ai’s marketplace reports a 1,200% rise in partner datasets in 2025 and several partners earning $1M+ per year (company figures; the revenue split is not published). Its published license terms are the clearest in the marketplace tier.

How to approach any of them

• Prepare a one-page data inventory: record classes, volumes, date ranges, systems of record, known PII — before any call. Our licensing guide has the checklist.
• Run the rights and consent audit first (hub, liability section). Deals die in diligence; undisclosed problems die expensively.
• Get two written offers. Published price-matches (Nyne) and tiers (Micro1) only work as leverage when a competing term sheet exists.
• Negotiate exclusivity separately and briefly; default to non-exclusive.
• If you run a data-acquisition program and want it represented accurately here, partner with us.