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Synthetic invoice reconciliation lab

Reconcile invoices with evidence before a person approves

Run a controlled three-document match using fictional data. Deterministic rules compare the invoice, purchase order and goods receipt; AI explains the evidence; a person makes the final decision.

Synthetic documentsReal rule engineHuman approvalNo accounting action

Interactive capability demo

Choose a scenario and inspect every decision

The documents are fixed, fictional examples. The server accepts only the scenario identifier—never a file, supplier record or confidential business document.

Synthetic scenario

Selected scenario

Exact three-way match

Fictional document · demonstration only

Supplier invoice

INV-DEMO-1048
Date
2026-07-28
PO reference
PO-DEMO-381
Supplier
Example Components Ltd · EU-DEMO-001
Buyer
Example Manufacturing Ltd · EU-DEMO-900
DescriptionQtyUnit priceTotal
Industrial sensor kit10€120.00€1,200.00
Subtotal
€1,200.00
Tax 20%
€240.00
Total
€1,440.00

Complete the security verification to run the server workflow.

One-hour review token · 24-hour private retention · no uploads · no production data

Rule result

Run the selected scenario to see authoritative checks, reason codes, the AI explanation and the human decision controls.

Control sequence

Automation handles evidence; a person controls the consequence

  1. 01

    Constrained intake

    Only one of three server-owned synthetic scenarios is accepted. There is no public upload path.

  2. 02

    Authoritative matching

    Supplier, PO, currency, quantity, price, total and duplicate rules determine the workflow state.

  3. 03

    Assisted explanation

    Gemini translates the fixed rule evidence into a concise reviewer summary; it cannot change the result.

  4. 04

    Human decision

    A short-lived hashed token authorizes approve, request-correction or reject actions.

  5. 05

    Controlled handoff

    Approval creates a clearly marked demo draft instead of writing to an accounting platform.

  6. 06

    Audit and expiry

    Each transition is recorded and the synthetic private record is automatically eligible for deletion after 24 hours.

Safety boundaries

Designed as a public capability demo, not an upload portal

No customer documents

The endpoint accepts a scenario ID only. Names, amounts and documents are created server-side and are explicitly fictional.

Rules outrank AI

Money, quantity and duplicate checks are deterministic. AI produces an explanation, never an approval decision.

Abuse controls

Turnstile, same-origin checks, request-size limits and a separate rate-limit bucket protect the public workflow.

Short-lived access

Review tokens are random and stored only as hashes. Sessions expire after one hour and records after 24 hours.

What this demonstration establishes—and what it does not

It demonstrates

  • A working server-side three-way match and reason-code engine
  • Visible evidence behind every pass, review and block state
  • AI assistance contained behind deterministic business rules
  • A real human decision and auditable state transition

It does not claim

  • A deployment inside a client's accounting or ERP system
  • OCR accuracy on arbitrary uploaded documents
  • Tax, legal or accounting correctness for a real transaction
  • A production payment, posting or supplier communication

Questions

How a real reconciliation project differs

Can visitors upload an invoice?+

No. Public arbitrary uploads would require malware scanning, document-isolation controls, stronger retention tooling and client-specific privacy terms. This demo deliberately accepts only synthetic scenarios.

Does AI approve the invoice?+

No. Deterministic checks create the pass, review or block state. Gemini only explains those results. A human records the final decision.

Can this connect to an ERP?+

Yes, in a client project after the ERP, supplier master, approval policy, authentication, logging and rollback requirements are documented. The public demo creates a non-posting draft only.

What would be measured in production?+

Touch time per invoice, straight-through match rate, exception reasons, duplicate prevention, correction cycle time, approval latency and reconciliation accuracy against a reviewed sample.

Have a document process with too many manual checks?

Describe the documents, systems, exception rules and approval boundary. We will assess where deterministic automation and supervised AI can safely help.

Request a free automation audit