Ingestion
Invoices arrive by email or upload and are stored securely with an audit trail.
Illustrative
Invoice processing automation
An AI-assisted pipeline that reads supplier invoices, validates them and posts clean data to the accounting system, with humans reviewing the uncertain ones.
- Sector
- Finance operations
- Service
- AI Automation
- Typical team
- Delivery lead, 1 AI engineer, 1 back-end engineer, part-time QA
The challenge
A finance team keys supplier invoices into the accounting system by hand. It is slow, error-prone, and the busiest weeks pull people away from higher-value work.
Approach
How we would tackle it
- 01
Start with the data you already have
Collect a representative sample of invoices, including the messy ones, and agree what counts as a correct result.
- 02
Build an evaluation set first
Label a test set so accuracy is measured, not guessed, and every change can be compared against it.
- 03
Keep people in the loop
Confident extractions flow through. Uncertain ones go to a review queue with the source document beside the proposed fields.
- 04
Monitor after launch
Track accuracy, review rate and cost per document, and retune as suppliers and formats change.
Solution
What gets built
Extraction
Language and vision models pull out supplier, dates, lines and totals into a strict schema.
Validation
Rules check totals, duplicates, tax and purchase-order matches before anything is posted.
Review and integration
A review queue for exceptions, then an API integration that posts approved data to accounting.
- Python
- TypeScript
- OpenAI
- Anthropic Claude
- PostgreSQL
- n8n
Timeline
Typical phases
1 week
Map
Pick the workflow, gather samples, define success.
2–3 weeks
Prototype
Working proof of concept measured on the evaluation set.
3–4 weeks
Integrate
Connect to email, accounting and the review queue with logging.
Ongoing
Monitor
Quality and cost tracking with scheduled improvements.
Goals
What we would aim for
Targets we would agree up front and measure, not results we claim.
- Most routine invoices processed without manual keying
- Exceptions surfaced clearly instead of buried in an inbox
- Accuracy measured against a labelled test set, not anecdotes
- Sensitive data handled with minimal exposure and full audit logs
Let's scope your project
Tell us what you're working on. We'll reply within one business day with next steps and a clear plan.