The business challenge
A logistics company receives invoices in several layouts from transport and warehouse vendors. Staff retype reference numbers, totals, and charges, then compare the invoice with purchase orders. Missing fields and price discrepancies create a slow cycle of follow-up messages.
The proposed approach
Use a document pipeline to classify invoices, extract an agreed set of fields, and apply deterministic checks against purchase orders. Present exceptions with the source document so accounts payable can confirm or correct the data before it reaches the accounting system.
What the scope would include
- Invoice ingestion from an agreed upload or mailbox channel.
- Structured extraction of vendor, invoice, tax, and line-item data.
- Validation of totals, duplicates, and purchase-order references.
- A review queue with an explicit approve or correct decision.
How the pieces connect
The proposed system separates document storage, extraction, business rules, and accounting integration. Approved records receive a unique processing reference to reduce duplicate posting. Integration failures remain visible and retryable.
Controls and exception handling
Low-confidence fields and failed validation checks require review. Access to invoice files is limited to the relevant team, and retention is agreed around business requirements. The processing log records corrections without treating extracted values as automatically authoritative.
Intended benefits
- Reduce routine manual entry for supported invoice formats.
- Surface discrepancies before records reach accounting.
- Give reviewers a consistent view of the document and the exception.
How we would evaluate it
Measure field-level extraction accuracy on representative documents, exception rates by layout, reviewer correction time, duplicate detection, and successful downstream posting.
Actual outcomes would depend on the available systems and data, agreed scope, user adoption, and results of the pilot.