Document processing

Document Intelligence

Extract, classify, validate and summarise information from contracts, reports, forms and operational documents.

The problem

Documents arrive in inconsistent formats and are processed by hand. The work is slow, hard to audit, and the error rate rises with volume.

Retrieval pipeline

  1. 1

    Source content

    Documents, wikis, ticket history

  2. 2

    Ingest and chunk

    Scheduled, with permissions captured

  3. 3

    Embed and index

    Vector plus keyword

  4. 4

    Retrieve

    Filtered to the asking user's access

  5. 5

    Ground and answer

    Model reads only those passages

  6. 6

    Cite and log

    Sources shown, quality measured

How a question becomes an answer grounded in your own content, with the permission filter applied before the model ever sees a passage.

How it works

  1. 1

    Documents are ingested from upload, email or a storage location and classified by type.

  2. 2

    Structured fields are extracted, with confidence scores attached to each.

  3. 3

    Extracted values are validated against business rules and reference data.

  4. 4

    Anything below the confidence threshold routes to a person for review rather than passing silently.

  5. 5

    Verified output is written to the target system, with the source document linked for audit.

What you should expect

  • Manual data entry reduced substantially
  • Consistent extraction with a measurable error rate
  • Exceptions surfaced rather than buried
  • A traceable link from every value back to its source document