INVOICE PARSING
Invoice parsing that returns clean, schema-validated fields
Talonic parses any vendor invoice into typed JSON: vendor, invoice number, dates, line items, tax, and totals. Every value comes back with a confidence score and a pointer to the exact region it was read from. No per-vendor templates to maintain, and no brittle rules that break when a supplier redesigns their layout.
What invoice parsing is
Invoice parsing reads an invoice and converts it into structured fields a system can act on: the supplier, the invoice and PO numbers, issue and due dates, currency, line items, tax, and the net and gross totals. Done well, it replaces the manual keying that sits between a received invoice and an entry in accounts payable.
The hard part is layout variance. Every vendor formats invoices differently, and template-based parsers break the moment a familiar supplier ships a redesigned PDF. Talonic parses against a schema rather than a fixed template, so the output shape stays constant even as the input layout changes. A new supplier you have never seen still maps to the same typed fields on the first try.
Fields a parsed invoice returns
- Invoice number and PO number
- Vendor name, address, and tax ID
- Invoice date and due date (normalized to ISO 8601)
- Currency and net, tax, and gross totals (as numbers)
- Line items: description, quantity, unit price, line total
- Payment terms, IBAN, and remittance details
Dates are normalized to ISO 8601 and amounts come back as numbers, each mapped to a stable key so the JSON shape is identical across vendors. Need a non-standard field, like a project code in a memo line? Add it to your schema and it parses alongside the rest.
How Talonic parses an invoice
Step 1
Upload or connect the invoice
Drop a PDF, scan, photo, or email attachment into the dashboard, or POST it to the /v1/extract endpoint. Talonic accepts 25+ formats including PDF, DOCX, XLSX, and common image types, so a phone snapshot of a paper invoice parses the same way a clean digital PDF does.
Step 2
Pick a schema or let it auto-detect
Send your own invoice schema to get exactly the field shape your system expects, or let Talonic classify the document and apply a matching schema automatically. Either path yields the same typed output contract.
Step 3
Receive JSON with confidence and provenance
Every parsed value comes back as a typed field with a confidence score from 0.0 to 1.0 and a provenance pointer to the page and region it came from. Values below your confidence threshold can be routed for review before anything is trusted downstream.
Step 4
Export or deliver to a system of record
Export the result as JSON or CSV, or deliver it straight to an ERP, accounting system, or data warehouse over webhook, S3, or SFTP. The same parse runs identically whether it is one invoice or ten thousand.
Confidence, provenance, and EU residency
Parsing without trust signals is guesswork. Talonic attaches a confidence score from 0.0 to 1.0 to every parsed cell, plus provenance: the page and region of the source invoice that produced the value. You set a threshold, auto-accept the values above it, and route the rest to a reviewer. That is how a logistics customer running a 930-document benchmark moved measured accuracy from 75% to 92% across review cycles without hand-writing rules.
Everything runs on EU-resident infrastructure: Microsoft Azure in Germany West Central with Mistral Large as the primary model. Data does not leave EU jurisdiction for customers who require it. Talonic is GDPR aligned and co-authored DIN SPEC 91491, Europe's first standard for AI-ready data at the schema layer.
Frequently asked questions
What is invoice parsing?+
Invoice parsing is the process of reading an invoice document and turning its content into structured, machine-readable fields: the vendor, invoice number, dates, line items, tax, and totals. Traditional parsing relied on fixed templates that broke whenever a vendor changed layout. Talonic parses by understanding the document against a schema, so a new layout from a new supplier still maps to the same output fields without a template rebuild.
How accurate is Talonic invoice parsing?+
There is no single accuracy number, because accuracy depends on document quality and the field. Instead, every parsed cell carries its own confidence score from 0.0 to 1.0 plus a provenance pointer back to the source region. That lets you gate on confidence: auto-accept high-confidence fields and send the rest for a quick human check. On a 930-document logistics benchmark, a customer measured extraction accuracy climbing from 75% to 92% across review cycles using exactly this confidence-gated approach.
Can it parse scanned or photographed invoices?+
Yes. Talonic handles scans, photos, and mixed-quality images alongside born-digital PDFs. The Capture phase normalizes the input first, then extraction runs against the schema, so a skewed phone photo and a clean PDF resolve to the same set of typed fields.
Where is invoice data processed?+
Processing runs on EU-resident infrastructure: Microsoft Azure in Germany West Central with Mistral Large as the primary model. Data does not leave EU jurisdiction for customers who require that. Talonic is GDPR aligned, and processing meets European standards for AI-ready data at the schema layer.
How do I start parsing invoices?+
Start free with no credit card: open the dashboard or get an API key, send an invoice, and read back the parsed JSON. For volume, paid usage is credit-based at 1,000 credits per euro. Developers can call the single /v1/extract endpoint directly or use the Node SDK and MCP server.
Start parsing invoices today
Send a sample invoice and read back the parsed JSON in minutes. Start free with no credit card, then scale on usage-based pricing.
Want the use-case view of accounts payable automation? See invoice data extraction. Building this into software? Use the data extraction API or the free invoice extraction tool.