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Documents in. Structured data out.
Service — Intelligent Document Processing
Invoices, delivery notes, contracts and forms still arrive as PDFs, scans and email attachments. We combine OCR with language models to read them, extract the fields you need, validate them against your rules and pass them into ERP, accounting or CRM, with a person checking only the uncertain cases.
From inbox to system of record.
From inbox to system of record.
What we build
Document capture & OCR
Reliable text recognition for PDFs, scans and photos, including tables, stamps and handwritten notes where the quality allows.
AI-based field extraction
Language models extract the fields you define, such as invoice number, amounts, dates, parties or contract terms, into a fixed schema.
Classification & routing
Incoming documents are recognised by type and forwarded to the right team, workflow or system automatically.
Validation against your data
Extracted values are checked against purchase orders, master data and business rules before anything is booked.
Stack
OCR, language models and solid integration.
Every field is measured, every correction counts.
Accuracy you can verify
Extraction quality is measured per field and document type against a labelled test set. Corrections made in daily review flow back into rules, prompts and test data, so the share of documents that need a person can shrink in a controlled way.
One document type at a time.
How we work
[Build]
[01]
Sample & defineWe collect representative documents, define the target fields and agree on accuracy goals and review rules.
[02]
Extract & measureA pipeline is built and measured against a labelled test set before it touches live data.
[Deliver]
[03]
Integrate & reviewConnection to your systems plus a review step for uncertain cases; your team keeps control over bookings.
[04]
Expand & improveMore document types and suppliers are added, guided by correction data from daily operation.
Further reading
Go deeper on this topic.
FAQ
Document processing, plainly answered.
Intelligent document processing combines OCR, machine learning and language models to read unstructured documents, extract defined data, validate it and pass it into business systems, replacing manual data entry.
Classic OCR turns an image into text. IDP also understands which text is the invoice number, the total or the notice period, checks it against rules and delivers structured data, even when layouts vary between suppliers.
Typical examples are incoming invoices, delivery notes, order confirmations, contracts, application forms and certificates. Each new document type is introduced with its own sample set and quality target.
Low-confidence fields or values that break a business rule are sent to a review step, where a person checks the document side by side with the extracted data before anything is posted.
Yes. OCR and language models can run with EU-hosted providers or self-hosted in your own infrastructure, depending on the sensitivity of the documents.
Yes. Structured e-invoices are read directly from their XML data, while PDF and scanned invoices go through extraction, so both arrive in the same validated format.
Which document does your team still type by hand?
Send us a few anonymised examples. We show you which fields can be extracted reliably and what a pilot would look like.
Get in Touch
Book an intro call.
Tell us about your project — we'll get back within 24 hours with a tailored proposal. No fluff, no boilerplate.
Pick a slot that suits you — or use the form. We reply within 24 hours on working days.
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