Training data for frontier AI labs. Written by people who can grade the answer.
The open web has already been trained on. What moves a frontier model now is work that does not exist yet: graduate-level reasoning written out in full, preference calls from people who can check a proof, and test sets no crawler has seen. eeko's data practice commissions that work from a vetted network of working specialists, verifies every item, and licenses it so your counsel can sign.
What is training data for frontier AI labs?
Training data for frontier AI labs is the human-made material a lab cannot get by crawling: demonstrations written by specialists, preference judgments from people qualified to say which answer is actually right, adversarial prompts in domains where a wrong answer hurts, and evaluation items that have never been published anywhere. It is the data that improves a model once the easy tokens are used up.
Frontier teams are not short of text. They are short of text that teaches something the model does not already know, and short of test sets they can trust. Both problems have the same root: once an item is on the public internet, there is no way to tell whether the model reasoned its way to the answer or simply recalled it. The only fix is work that is new, made to order, and kept off the web afterward.
That is what eeko's data practice supplies, with the same discipline behind our enterprise AI agents and AI infrastructure work: a written spec, a pilot batch, named reviewers, and a verifiable record on every item. See the wider AI training data practice and how every item is verified.
Three problems more tokens do not fix.
Each shows up as a flat eval curve. Each is a data problem with a data answer.
Expert-written SFT, preference, and evaluation data, to your spec.
Six things frontier labs ask us for most. Each starts from a written specification and a pilot batch, and is held to the bar you agree after the pilot.
- Step-by-step traces, not just final answers
- Second-expert pass on every hard item
- Pairwise, ranked, and rubric-graded
- Disagreement preserved, not averaged away
- Never published, never resold
- Near-duplicate check before delivery
- Domain-specific attack surfaces
- Graded safe and unsafe responses
- Human origin checked at intake
- WebDataset or COCO delivery
- Same network, same review bar
- Volume pricing from the first renewal
Human-made training data from people who do the work.
The eeko expert network is built around fields where correctness can be checked, and staffed by people who can check it.
Fields we staff for frontier work
- Mathematics — proofs, derivations, and competition-level problems, written and graded by mathematicians in the network.
- Medicine — clinical reasoning, differential diagnosis, and safety-critical dosing prompts from practicing clinicians.
- Software — code, architecture decisions, and review traces from senior engineers.
- Chemistry, law, finance, and language — synthesis routes from working chemists, statutory reasoning from attorneys, valuation logic from analysts, and acceptability judgments from linguists.
Every contributor is credential-checked before their first task. Every label records its source: the author, an AI suggestion, or an expert reviewer. You can filter on that in training.
What one reasoning trace carries by the time it reaches you.
An illustrative item lifecycle. The same checks run on every item, and the audit trail is hash-chained so nothing can be edited later without leaving a mark.
From capability gap to delivered batch.
Fixed scope and a fixed price once the spec is written. Nothing scales until the pilot batch has been through your pipeline.
Frontier AI training data questions.
How is frontier lab training data different from web-scraped data?
Scraped data is whatever happened to be published, under rights nobody checked. Frontier lab training data from eeko is commissioned: a specialist writes or grades each item against your rubric, a second specialist reviews the hard ones, and the item carries its own consent record, licence, fingerprint, and signed provenance. The content is new, so it cannot already be in your pre-training mix, and the paperwork is complete, so your counsel does not have to guess.
How do you stop evaluation data from leaking into training sets?
Three ways. The items are written for you, not gathered from anywhere public, so there is no original to leak. Each one is hashed at intake and compared against our registry, which surfaces duplicates and near-duplicates before delivery. And the set ships under an exclusive licence, so we never offer it to another buyer. The signed receipt names each item by ID and hash, a reference to check against if you ever suspect a leak.
Who writes frontier model training data at eeko?
Working specialists from the eeko expert network: physicians, mathematicians, software engineers, attorneys, chemists, linguists, and financial analysts, among others. Each one passes a credential check before taking a task, and identity is verified before payment. Your dataset spec names the field and seniority required, so a graduate-level proof is graded by someone who has written graduate-level proofs. Each label states its source: the author, an AI suggestion, or an expert reviewer.
How much does expert-written training data cost?
The price follows four things: the expertise an item needs, the time it takes to write or grade, how deep the review goes, and the licence. A long reasoning trace with a written rationale and a second-expert pass costs more than a quick pairwise preference call. Exclusive rights cost more than shared rights. Volume and standing orders pull the unit price down. We quote a fixed price once the spec is written, after the scoping call.
Can we train commercial models on the data?
Yes, inside the licence you agree to. Every item records its AI-training permission, the licence terms, and whatever model or property releases apply. Items that show an identifiable person are released for training only when that person's consent is on file. We hand your legal team the full documentation chain from contributor to delivery; they decide whether it fits your intended use. We provide the record, not legal advice.
What file formats do you deliver frontier datasets in?
JSON Lines, CSV, Parquet, WebDataset, COCO, and Croissant metadata. Text-only work usually goes out as JSON Lines or Parquet, and multimodal corpora as WebDataset shards. If your loaders expect a particular schema, we write it into the spec and the pilot batch arrives in that layout. Each delivery comes with per-item provenance records and a signed receipt.
How long until the first batch arrives?
A real person replies within one business day of your request. The scoping call turns your capability gap into a written spec, usually inside a week. A pilot batch follows so you can run the data through your own pipeline before committing to volume. Production timelines depend on how rare the expertise is and how long each item takes; we put the dates in the spec rather than promising a number before we know.
Training data by industry.
Solutions and experts frontier labs use most.
Tell us what the eval keeps getting wrong.
Send the capability gap in a few sentences. Inside one business day you hear back from a data lead with questions, an initial sourcing plan, and a path to a pilot batch. No deck. A ranked list.
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Markets served.
As an enterprise AI agency, eeko systems delivers production AI systems remote-first across the United States and internationally — including these markets: