Document preparation
Turn document collections into structured, reviewable material ready for search, retrieval, or model evaluation.
- OCR review and correction
- Metadata and taxonomy
- Structure and semantic chunking
- Duplicate and quality checks
AI Data Services
Make knowledge usable, reviewable, and traceable.
We prepare document collections and evaluation data for retrieval and AI-assisted systems, with explicit quality criteria and human review.
RAG data and evaluation
Prepare evidence-led retrieval datasets and test whether answers remain relevant, grounded, and traceable to source.
- Question and reference sets
- Retrieval relevance review
- Citation verification
- Failure and edge-case analysis
AI output review
Apply explicit rubrics and human judgement to compare, classify, correct, and improve generated responses.
- Response ranking
- Factuality and consistency checks
- Prompt-response refinement
- Structured review records
A bounded first engagement
Prove the workflow on a representative sample.
Start with enough material to expose structural and quality problems before committing to full-scale processing.
- DefineAgree the material, purpose, schema, acceptance criteria, security boundaries, and permitted use.
- PrepareProcess a representative sample and record assumptions, exceptions, and provenance.
- EvaluateMeasure quality against a reviewed reference set rather than relying on demonstration alone.
- DeliverProvide the prepared data, findings, and a reproducible account of what was done.
Bring the source material
Discuss a pilotBegin with one real collection.
Tell us what the documents contain, who needs to use them, and what a trustworthy result must make possible.