Dependable document analysis separates evidence location, extraction, interpretation and judgement. If these stages are mixed, plausible claims can no longer be traced to the original.
What the concept actually means
Before analysis, document type, version, language, tables, annexes and confidentiality are clarified. Structured questions and an evidence-linked output format follow.
Why it matters in the enterprise
For repeated processing, ad-hoc sampling is insufficient. Representative test documents, known expected values and rules for unreadable or conflicting passages are required.
A controlled method
The CTPM practice framework for controllable AI applications uses seven stages: understand the task, clarify context and data, apply AI deliberately, review professionally, handle deviations, approve accountably and document transfer. It is a transparent working framework, not a certification.
- Define task and impact
- Clarify data, context and permissions
- Review against domain criteria
- Control deviations, approval and evidence
CTPM practice example
CTPM practice example: Obligations are extracted from 30 policies. Each row contains document, version, section, original quote, normalised obligation and uncertainty. Grouping occurs only afterwards.
Quality and test criteria
The following criteria make quality observable for this use case:
- Completeness is measured against known evidence.
- Quotes match exact wording and location.
- Tables and annexes are reviewed separately.
- Unreadable passages are not silently completed.
Risks and common misconceptions
Risks include OCR errors, wrong document versions, omitted tables, mixing commentary with normative text and unauthorised processing of confidential content.
Example transfer artefact
Transfer artefact: a document-analysis template with source inventory, extraction schema, review sample and approval rule.