Data · Structuring

AI data structuring

Much of your company’s information lives in documents: invoices, contracts, purchase orders, emails, scanned forms. With AI we turn it into structured, validated data connected to your systems.

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The problem with unstructured data

Business systems need data in fields and tables, but information arrives as PDFs, photos, emails or files in different formats. Someone has to read and type it, and time and accuracy are lost along the way.

Traditional OCR tools read the text but do not understand the document: they rely on fixed templates and break when the layout changes. Language models do understand the content and can extract the right fields even when every supplier uses a different design.

The result is information you can search, analyse and use in automated processes, with human review only where it is really needed.

What we structure

Invoices and receipts

Supplier, tax ID, dates, amounts, taxes and line items, validated against your rules and purchase orders.

Contracts

Parties, term, amounts, penalties and renewals, searchable without opening each file.

Scanned documents and forms

OCR plus content understanding for records, applications, delivery notes and ID documents.

Emails and messages

Orders, complaints or requests arriving by email turned into categorised records.

Messy catalogues and records

Product, customer or supplier descriptions normalised and classified.

Validation and human review

Business rules and confidence levels: doubtful cases go to a review queue, the rest flows automatically.

How it works

01

Capture

Documents arrive by email, shared folder, form or integration with your systems.

02

Extraction

OCR and language models identify the document type and extract the fields into a defined schema.

03

Validation

Formats, totals, dates and matches with your records are checked; doubtful cases go to review.

04

Integration

Validated data is loaded into your ERP, database or ETL flow, linked to the original document.

Technology

We combine OCR and language models on Microsoft Azure, with outputs in formats your systems already understand.

  • OCR for PDFs, images and scans
  • Large language models (LLMs) to understand and extract
  • Output schemas in JSON, tables or straight into the ERP
  • Business validation rules
  • Human review queue and traceability

Teams that benefit most

  • Finance and accountingInvoice entry and matching with purchase orders.
  • LegalReviewing and searching contract clauses.
  • Operations and logisticsDelivery notes, orders and shipping documents.
  • Customer serviceClassifying requests and complaints received by email.

Timeline and engagement

We start with a pilot on the most frequent document types to measure accuracy with your own files before scaling up.

The solution can run on its own or as part of an ETL flow or an AI agent.

Case studies

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Frequently asked questions

How is this different from traditional OCR?

OCR turns the image into text. AI also understands what each value means, so it works with different layouts without a template per supplier.

What if the AI is not sure about a value?

Each field has a confidence level and validation rules. If it does not pass them, the document goes to human review before reaching your systems.

Does it work with scans or photos?

Yes, as long as they are legible. We check this in the pilot with real samples from your company.

Where are the documents stored?

In your cloud environment or the one we agree with you, with access control and traceability from each value to its original file.

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Lots of information trapped in documents?

Send us the document types you handle and we will show you in a video call how they would look as structured data.

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