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PATTERN

Invoice processing with vision AI

Receipt → vision LLM with context prompt → validation table → human approval → export to your target system.

Incoming receipts land structured in accounting — with a human-in-the-loop for edge cases instead of blind trust in the model.

When this pattern fits

Three pain points where the effort pays off.

  1. Incoming receipts land in the in-tray and take days to arrive structured in accounting.

  2. Data quality varies: handwriting on hospitality receipts, folded parking tickets, photographed slips.

  3. AI on its own recognises — but no one wants to hand it blind approval before payment.

How the pattern is built

Five steps, from input to filing.

  1. Receipt

    PDF, photo or scan — wherever from.

  2. Vision LLM

    Structured extraction with context.

  3. Validation

    Review table with confidence scores.

  4. Approval

    Human decides on edge cases.

  5. Export

    SEPA, DATEV or booking CSV.

Live example

From real operations.

Customer Danumed BELEGVERARBEITUNG

From a stack of incoming invoices and expense receipts, the tool produces an import-ready SEPA transfer file for the banking software in minutes — with human review before every payment.
See the case

What is deliberately out of scope

Three places where we leave it to a person.

  • Fully automated payment release. Before every bank transfer, a human review stands.

  • Recognition decisions without justification. Every extracted value comes with a confidence and a source image.

  • Specialist receipts without a human eye. Complex cross-border invoices or disputes escalate by design.

Typical project scope

Discovery → pilot → rollout.

  1. Discovery

    One to two weeks. We understand your concrete bottleneck, look at the available sources and decide together whether the pattern is really the right answer here.

  2. Pilot

    Four to eight weeks. A scoped variant on real data, with a small user group. Dry-run before every write, clearly defined success criteria.

  3. Rollout

    From two months onwards, fluid. Extension to further sources, teams or sites. Hand-over to operations with documented architecture and training for those responsible.

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Two doors, one address.

Specific bottleneck?

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Demo with your own data is possible. We bring the pseudonymisation set up and ready.

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