Training-data production
Expert answers, demonstrations, annotations, original collection and human feedback for a defined model or workflow need.
What you receive
Versioned records, task instructions, metadata and a quality report.
Human work.AI progress.
Training data, licensed datasets, agent environments and independent evaluations. We turn a defined requirement into work your team can inspect, use and build on.
Four ways forward.
Proprietary-data licensing
A defined subset of authorized records, prepared for explicitly permitted uses.
What you receive
A scoped dataset, source and rights manifest, transformation log and exclusions.
Agent environments
Resettable environments with representative tasks, tools and inspectable scoring.
What you receive
A bounded sandbox, reference trajectories, tests and integration documentation.
Model evaluations
Independent tests of model and workflow behavior against customer-defined criteria.
What you receive
A held-out test pack, expert rubric, failure analysis and reproducible report.
Compare the deliverables.
Training-data production
Your team needs examples or human judgments that a general-purpose dataset does not provide.
- Records in the agreed format, with the required labels, answers or judgments.
- Versioned instructions, rubric and relevant collection metadata.
- Review results, accepted quantities and a correction log.
From brief.
To handoff.
Agree the work, review the output and receive the deliverable with the information your team needs to use it.
- 01
Start with the right question.
Tell us the model capability, data need or workflow you want to address. Together we define the deliverable, intended use, source rights and acceptance criteria.
- 02
Build around your requirement.
We create or prepare the agreed deliverable using the project instructions and approved sources and tools. For data-production work, a paid sample establishes the review standard before the full batch.
- 03
Make quality inspectable.
Independent reviewers check the work against the agreed criteria. Review findings, corrections and unresolved issues are documented for the delivery version.
- 04
Review the delivery.
Receive the versioned deliverable with its quality report, permitted uses and known limitations. Your team reviews it within the agreed acceptance period, with corrections handled under the project terms.
Your next
AI project.
Tell us what you need to train, license, build or evaluate.