Document AI
An AI document assistant with human review
Turn approved documents into a working tool for retrieval, fact extraction, classification and draft preparation with source references.
Discuss your project →Work the assistant can support
The use case fits repeatable review of contracts, applications, procedures, correspondence or technical materials. An assistant can locate a passage, extract agreed fields, classify a document or prepare a draft. Accountable people retain the final decision and review critical facts.
- Retrieval with a link to the specific source
- Extraction of agreed fields and attributes
- Classification and routing
- Draft responses, findings or summaries
What a pilot requires
We define one document class, a representative example set, permitted users and reference answers. Versioning, languages, scans, confidentiality and retention are assessed separately. This evaluates quality on real work rather than a prepared demonstration.
How output is controlled
An answer exposes the source used or states that evidence was not found. Actions in external systems require agreed permissions and approval points. The pilot ends with an error log, evaluation set and a decision for the next iteration.
Fit before scope
Is this the right starting point?
Use these criteria for an initial orientation. The final recommendation follows a review of your context, data and constraints.
A good fit when
- A process or decision that needs improvement is identified
- An accountable sponsor and result user are available
- A measurable outcome or quality criterion can be defined
Resolve this first when
- The goal is simply to buy unspecified AI without a defined challenge
- A guaranteed impact is expected before data are assessed
- No one is accountable for accepting the result
A verifiable first stage
What you can use to make the next decision
The exact scope is agreed before work begins. These are typical decision artefacts, not promised business results.
AI use-case matrix
Challenges compared by value, data availability, risk and ease of verification.
Pilot boundary
One process with defined users, sources, human oversight and stop conditions.
Decision criteria
Quality measures and a process to scale, refine or stop the initiative.
Five questions · no datasets or credentials
Frequently asked questions
Frequently asked questions
Must we upload every company document?
No. A pilot should focus on one process and an approved document set large enough to evaluate quality.
Can the assistant answer without a source?
Where verifiability matters, an answer should cite its source or explicitly state that supporting evidence was not found.
How are scanned files handled?
We first assess recognition quality, page structure and critical fields. OCR errors are measured separately from AI-answer quality.
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