Supporting capability
Turn documents into fields your team can use.
We extract structured information from PDFs, scans and business documents, with schema validation, source references and a review path for uncertain results.
Understand the documents
Sample the layouts, languages, scan quality and fields that matter. Compare OCR, native text extraction and model-based extraction where appropriate. Define the acceptable error level for each field.
Extract and review
Return fields in an agreed schema, validate totals and formats, and attach document or page references. Flag missing or conflicting information for a reviewer. Avoid treating a plausible model response as a verified fact.
Connect the next step
Send approved results into a database, CRM or operating workflow. Scope access controls, retention, review ownership and monitoring. Processing sensitive records requires an agreed provider and data-handling arrangement.
Where this fits
Document AI produces structured records from documents. RAG retrieves passages to help answer questions; it is not a replacement for field-level extraction and validation.
Operations automation: see the wider workflowEvidence and further reading
See this in an industry workflow
Explore proposed applications and fictional demos. These are not claims of completed projects in those industries.
- Specialty distribution
RFQs, order entry, catalog data and sales operations with human review.
RFQ-to-quote demo - Commercial insurance
Submissions, renewals, document handling and agency handoffs with accountable review.
Insurance submission demo - Property management
Maintenance intake, approved vendor coordination and staff-reviewed completion.
Property maintenance demo
Define the scope before committing to a build.
Start with a free conversation about your requirements. A well-defined project can go straight to a proposal. If we need to investigate the data, systems or risks first, we quote discovery separately. Implementation, usage fees and support depend on the agreed scope.