AI Agents & Workflow Automation
Classification, drafting, routing and workflow steps with a person in the loop where it matters.
Document Processing
We turn documents you already receive into structured data: invoices, forms, receipts, IDs and the semi-structured files that sit between them.
The problem
Most of this work starts with a pile that already exists: invoices in an inbox, forms photographed on a phone, receipts, identity documents, or a mix of PDFs that look similar until a supplier changes the layout.
Some of those are structured and barely need a model. Some are semi-structured: the fields exist, but not in a fixed place. Some are awkward scans. The service is to classify the document, read it, and produce fields the next system can use — with a check where the read is uncertain.
OCR is part of that, not the whole of it. Reading the characters is the start. Knowing which characters are the invoice number, and whether that number is trustworthy enough to post, is the rest.
Supplier, dates, totals, tax and line items, where the document actually contains them.
The fields a process already expects, including forms that are filled by hand or photographed.
The fields a process is allowed to collect, handled as sensitive data rather than as ordinary text.
Decide what kind of document arrived before trying to read it as the wrong thing.
Use character recognition and a model where the layout is not fixed, and a simpler parse where it is.
Check totals, required fields, formats and obvious contradictions before the data moves on.
A record the next system can store, not a paragraph about the document.
Send a confident result onward, and hold an uncertain one for a person.
The sequence is the same. The amount of human checking depends on the document and on what a wrong field would cost.
Accept the file from the inbox, upload or system that already collects it.
Decide the document type, and stop if it is not one the process handles.
Read the agreed fields. Prefer a fixed parse when the layout is stable.
Check the result against rules, and against the document when a person needs to see it.
Write the structured record to the system of record, or return it for review.
Validation
We do not claim 100% extraction accuracy. A clean digital invoice and a photographed receipt are not the same problem, and a model that is usually right will still misread a total, a date or a name.
So the design includes a threshold. Some documents can pass if the fields validate. Others must be shown to a person with the original beside the extracted values. Which is which depends on the document and on the business requirement — a misread internal reference is not the same risk as a misread payment amount.
Identity documents need extra care: collect only the fields the process requires, restrict who can see them, and do not treat a successful read as proof of identity by itself.
Once the fields are trusted enough to move, the destination is usually an existing business system. If the next step is to route or raise a task, that is an agent workflow taking the structured result, not the scan.
We choose the lightest method that reads the document reliably. A model is not automatically better than a parser.
A document is only useful once a workflow or another system can act on the fields.
Classification, drafting, routing and workflow steps with a person in the loop where it matters.
APIs, data movement and connections between business platforms.
Practical AI capabilities and automation inside existing workflows.
No. We scope the types you actually receive. A new layout or a type outside that set should be held, not forced into the wrong fields.
No. Validation and review are part of the service. How much review you need depends on the document and on the cost of a wrong field.
Only if the process requires it, and only with the access limits that implies. Reading an ID is not the same as keeping a copy of it.
Whether you're building something new, modernising an existing application or need specialist development support, let's discuss what you need.