Your schema, not the model’s interpretation.
Your organization defines what data it needs and in what form. The AI extracts according to that definition, not according to what it considers relevant.
Governed Extraction
AI-extracted data you can trust.
Extract exactly the information your business needs from your documents, with the accuracy of a controlled process and the speed of AI.
The problem
Extracting data with AI is easy. Getting it right is not. A case number with one wrong digit, a rounded amount or a tax ID reconstructed “from memory” can invalidate an entire process. In regulated sectors, almost-correct data is incorrect data.
Pillars
Literal accuracy.
Identifiers, references, amounts and dates are copied exactly as they appear in the document, never reconstructed from memory.
Automatic when it can be, human when it should be.
Whatever meets your rules flows through on its own. Anything doubtful stops and goes to a person for review before it reaches any system.
Every value, with its source.
Every extracted value points to its source document. Auditing means opening the original.
How it works
Define
what information you need to extract.
Process
documents continuously: what is reliable moves on by itself, and what is doubtful waits for review.
Integrate
verified data into your systems and your GDC.
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Want to apply GenInContext to your situation?
The website explains the overall proposition. The assistant can help you relate it to your stack, your use case and your AI maturity level.
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