Training data for AI teams. Built to the spec, not pulled off a shelf.
You know what the model should be able to do and where the current data lets it down. Tell us that, and we go and get the data: from the eeko creator catalogue, from credential-checked experts, and from paid capture programs. Every item is verified before you see it and licensed in writing when you do. Pilot first, volume after, standing orders when it works.
What training data for AI teams means at eeko
Training data for AI teams means two things at eeko. First, custom datasets: data that does not exist yet, or exists only in people's heads and hands, commissioned to a written spec and delivered verified. Second, expert annotation of data you already hold, done by people qualified in the subject rather than by whoever is cheapest this quarter.
We came to this as builders, not brokers. eeko ships enterprise AI agents and retrieval systems into banks, hospitals, and law firms, and the fine-tuning and evaluation data those systems need has to clear the same bar as the systems themselves. When we could not buy it, we built the supply and ran it like an engineering practice: a spec before sourcing, acceptance criteria per item, a pilot before volume, and a record on everything delivered.
That record is the part most vendors skip. Each item we deliver carries a cryptographic fingerprint, an origin check, a consent reference, the identity of whoever labeled it, a signed provenance record, and an independent timestamp. When your counsel, your regulator, or your customer asks where the training data came from, you hand them the verification record rather than a vendor's assurance.
Custom AI datasets for every stage of the model.
Six things AI teams most often ask us for. Each is sourced the same way and held to the same acceptance criteria.
Start small. Scale on evidence.
Real samples land before anything scales; every later batch is held to the acceptance criteria you signed off in the pilot.
Expert data annotation on data you already have.
Half the requests we get are not for new data. They are for better labels on data the team already owns.
How the labels are made
- Matched by field — clinical notes go to clinicians, contracts to attorneys, imaging to radiologists, code to software architects. Browse experts by field.
- Rubric first — your labeling guide is turned into a rubric with examples, piloted on a sample, and revised before volume.
- Author on every label — each label records who wrote it, and labels are tagged by source: expert-reviewed, owner-stated, or model-suggested.
- Second pass — an agreed share of every batch is independently re-labeled and the disagreement rate is reported to you.
- Your licence, your data — annotation of your data never changes who owns it; the labels come back under your terms.
Whatever the model takes in.
Seven modalities, one intake
- Text and reasoning — demonstrations, rubrics, preference pairs, and multilingual sets written by people who practice the field.
- Audio — released recordings with verbatim transcripts and phonetic labels.
- Image and video — originals with releases, origin checks, frame hashes, and expert captions.
- 3D and CAD — scans, meshes, and drawings with units.
- Documents and records — contracts, filings, and tables with a schema and personal data masked.
- Robotics — teleoperation and sensor streams with reviewed success labels.
Delivered the way your pipeline already reads.
Labels, technical metadata, origin, consent references, and the hashes to check every file, in the format you train on today.
A dataset off the shelf, or one built for your model.
Collected for someone else's problem, labeled by an anonymous crowd, licensed on terms you did not negotiate, and silent about where it came from. When the model's needs change, you shop again.
- Fit Approximate, by accident
- Labels Crowd, no author, no second pass
- Rights Boilerplate, disputed later
- Proof A folder and a promise
Sourced against your spec, labeled by verified experts with a second pass, licensed for the uses you name, and shipped with a per-item record and a signed receipt. When the model's needs change, the same network delivers the next batch.
- Fit Written spec, pilot-tested
- Labels Named experts, agreed review share
- Rights Licence scoped per use, exclusivity optional
- Proof Fingerprint, consent, signature, timestamp
Training data by industry.
Who may label the data and what consent requires both depend on the domain. Pages for the teams that ask us most often; the full list is under training data by industry.
Verified training data your counsel can sign off.
Buying training data questions.
How is training data priced?
Five things move the price: the modality, how specialised the people doing the work must be, the volume, the licence term, and whether you want the work closed to other buyers. Items already in the catalogue carry the training price the owner set. Commissioned work gets quoted against the written spec, fixed scope and fixed price, with a pilot batch costed separately so you can stop after it if the data is not right. Larger standing orders get volume terms.
Can we get exclusive rights to a dataset?
Yes. An exclusive licence keeps the work away from every other buyer for the term you choose, and the exclusivity is reflected in the quote and spelled out in the licence itself. Commissioned datasets are the usual candidates, since they were built for your capability in the first place. Catalogue items can also be licensed exclusively where the owner agrees. Non-exclusive licences cost less and suit general corpora.
How is personal data handled in training datasets?
Documents and structured records are scanned for personal data before delivery, and anything found is masked, with the masking logged on the item. Images, audio, and video that show an identifiable person are only offered when that person's release for AI training is on file. Location metadata is removed at intake. If your use case needs identifiable data, such as speaker-tagged audio, the consent is collected for that purpose specifically.
Can we integrate with eeko programmatically?
Approved buyers receive an API key. With it you can search the curated selections we have prepared for you, place and track orders, post new requests, pull exports in your chosen format, and manage standing orders that push newly matching, verified work to you on a schedule. Every export includes the item hashes and the signed receipt, so your pipeline can verify what it ingests.
How big is a pilot batch, and can we reject it?
The pilot size is agreed in the spec and is deliberately small: enough to run through your pipeline and measure, not enough to commit you. You judge it item by item against the acceptance criteria you approved. Reject what fails and tell us why; we adjust the spec or the sourcing and run the pilot again if needed. Production starts only when the pilot passes, and the same criteria apply to every batch after it.
What if the data we need does not exist yet?
That is the usual case. When nothing in the catalogue fits, we commission it: domain experts write, label, or grade new examples to your rubric, workers in the capture programs record real tasks to a written protocol, and creators make new work on licence terms settled before they start. You see samples before the commission scales, and the finished set is verified and licensed exactly like catalogue work.
Can you annotate data we already hold?
Yes. Send your own text, documents, images, audio, video, 3D files, or robot episodes and we label them to your rubric. Tasks that need a specialist go to a credential-checked expert in that field, every label records who made it, and a second expert reviews an agreed share. Your data stays under your licence; the labels are delivered back in your format with a signed receipt. See data annotation services for the task types we run.
Explore the data practice.
Brief us on the capability. We will find the data.
Send a dataset request, or book a thirty minute scoping call. Inside one business day a data lead comes back with questions, a first sourcing plan, and a date for the written spec. No deck. A spec, a pilot, and a price.
Experienced within
Markets served.
As an enterprise AI agency, eeko systems delivers production AI systems remote-first across the United States and internationally — including these markets: