AI Data Collection
Training data gathered to a written specification — the right volume, the right distribution, and a record of where every item came from.
What is included
AI Data Collection, in detail
Specification first
Volume, class balance, edge cases and acceptance criteria agreed in writing before collection starts.
Multi-source sourcing
Public, licensed and commissioned sources combined to hit the distribution you need.
Provenance tracking
Every item carries its source and licence so your dataset survives a legal review.
Quality sampling
Statistical sampling at agreed checkpoints rather than a single check at the end.
Delivery in your format
JSONL, Parquet, COCO or whatever your pipeline expects, with a schema document.
How we work
Four steps, no surprises
- ConsultationWe learn the business and what success looks like.
- Audit & scopeA written plan: what we build, in what order, at what cost.
- BuildDelivered in stages you review as we go.
- SupportMonitoring and iteration once it is live.
Questions
Frequently asked
Can you collect data in languages other than English?
Yes. We scope language coverage and native-speaker review up front, because a non-native pass on annotation is worse than no pass.
Who owns the collected data?
You do. We deliver it with the licence position documented per source.
More Data services
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Cleaning, normalising, deduplicating and structuring raw data so it is genuinely fit to train on.
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Learn more →AI Model Validation
Human evaluation of model outputs against defined rubrics, producing scored, reviewable and reproducible results.
Learn more →Environmental Metrics Research
Emissions, energy and resource-use data gathered from disclosures and standardised across entities for comparison.
Learn more →Social Data Research
Workforce, community and supply-chain indicators researched from disclosed sources and structured for ESG scoring.
Learn more →