Safer RAG inputs
Remove identifiers and unrelated fields before approved content reaches chunks, embeddings and model context.
USEFUL DATA FOR MODELS, RAG AND ANALYTICS
Prepare approved unstructured content for retrieval and analysis, and create synthetic evaluation sets that measure performance beyond a demo dataset.
For AI & Data Teams
The model is only one component. Reliable enterprise outcomes require representative inputs, explicit expected behavior and evidence when something changes.
Remove identifiers and unrelated fields before approved content reaches chunks, embeddings and model context.
Measure extraction, transcription, citation, decision and privacy behavior across realistic multimodal scenarios.
Reduce dependency on production access when exploring new models, prompts and workflow designs.
Questions your data should answer
Product fit
Use real examples only when they are necessary. Use synthetic scenarios to scale coverage and repeatability.
Detect, review, remove and verify sensitive information according to a defined downstream purpose.
Generate realistic documents, images and audio with labels, expected results and controllable variation.
Start with the blocked workflow
Show us the source content, workflow and downstream users. We’ll identify where redaction, synthetic data or a different control is actually appropriate.
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