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Case study

Reducing manual data entry in expense processing

Manual data entry created delays at month end, inconsistent coding and no reliable audit trail between the document and the ledger entry.

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Finance & AccountingResearch & InnovationSubmitReceipts

Challenge

Receipts and invoices arrived as photos, PDFs and email attachments and were re-typed into accounting tools by hand.

Approach

  • Catalogued incoming document formats and failure cases
  • Built an extraction pipeline with confidence scoring and a human review queue
  • Standardized categorization and approval routing
  • Designed export paths toward accounting platforms

Solution

An AI-assisted document pipeline that captures receipts, extracts structured fields, routes low-confidence items for review and keeps the original document linked to the record.

Implementation

  1. 01Document sample analysis
  2. 02Extraction pipeline and accuracy evaluation
  3. 03Review queue and approval workflow
  4. 04Pilot with real expense batches

Key outcomes

  • Structured expense data captured from mixed-format documents
  • Low-confidence extractions routed to human review instead of failing silently
  • Original documents retained alongside every record

Only verified outcomes are published. Performance metrics appear here when the client has approved them.

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