Document processing turns contracts, invoices and knowledge bases into structured data and instant answers: OCR and layout models pull the fields, a RAG agent classifies and validates them, clean output flows into your systems, and anything below the confidence threshold goes to a person. Accuracy on structured fields is typically 95–99%, and scans and phone photos are in scope.
People rekey invoices and forms into systems — slow, costly, error-prone.
Documents queue for days waiting for a human to classify and route them.
Answers exist in PDFs and wikis no one can find when they need them.
Manual handling leaves gaps that fail compliance and reviews.
Documents arrive from email, upload, or a watched folder.
OCR and models pull fields, tables, and entities.
A RAG agent classifies, validates, and answers questions over them.
Structured output flows to your systems, with human sign-off on exceptions.
Every field comes with how sure the model is. Anything below your threshold goes to a person instead of into your system of record.
Totals, tax, supplier, contract terms and duplicates are checked against the ERP and your policy before anything is posted.
Answers over your document base arrive with the document, the version and the paragraph, so verifying one takes seconds.
What was read, what was extracted, who approved it and when — exportable, which is what makes the whole thing usable inside a regulated process.
100–300 examples including the awkward ones: bad scans, foreign languages, formats a person struggles with.
API or import access to the ERP, DMS or accounting system the result has to land in.
What makes a document valid, who approves what, and what must never be posted automatically under any circumstances.
At a few dozen documents a month, a template and a person beat a build on cost.
Handwriting on unstructured forms is still read unreliably enough that we will not sell it to you as automation.
If nobody can state the approval rules, extraction will be accurate and the process will still be wrong.
Each page states the workflow, the systems it integrates with, what it costs and when it is the wrong choice.
Reads incoming invoices, checks totals, tax and supplier against the ERP, and posts only what clears the rules.
Sorts mixed incoming documents by type and routes each one to the queue, folder or system that owns it.
Answers questions across your contract base with the document, version and clause attached to every answer.
document sets with errors
Client under NDA. The figures are the client’s own, comparing the periods before and after launch.
Full audit + a working pilot on one slice of the process. Fully credited to the build.
Full rollout with monitoring, escalation, and documentation. Priced on scope.
Ongoing tuning, new scenarios, and monthly reporting. Cancel anytime.
Typically 95–99% on structured fields, with confidence scoring and human review routed for anything below threshold.
We don’t propose an off-the-shelf product either. The audit is there precisely to see where your process differs from the ordinary one, and the build is shaped around that difference. And if it turns out a standard tool covers you well enough, we’ll say so plainly — the process map stays with you in any case.
It’s a fair thing to ask, and responsibility matters more here than accuracy. A person answers for it, and the system is built so that they can: a doubtful case is never posted quietly, it goes to a review queue. Low confidence isn’t an error for us, it’s a route. Around 70% clears straight through and a person looks at the rest — and where exactly that line sits is yours to decide.
That’s a common requirement, and a reasonable one. We fit the setup to your data rules: if nothing may leave, the model runs locally inside your own perimeter, and the documents never cross it.
That’s not unusual, and it’s fine. Integrating without an API is the most underestimated line in a quote, which is why integration surface comes first among the four cost drivers, and why we don’t name a fixed price before the audit. Working without an API is perfectly possible — files, exports, email — it simply costs more, and it’s better to know that early. Which is why, fairly often, we build the API for you.
It happens often, and usually for one reason: the pilot was measured on the happy path and the exceptions were left for later — though the exceptions are where most of the work turns out to be. So we look at the share that clears without a person rather than at extraction accuracy, and we agree in advance who handles the rest, and how.
No, that isn’t what this is about. What goes is the retyping, not the people: decisions stay with a person — the disputed document, the non-standard transaction, the conversation with the client, the signature under the reporting. On one accounting project, closing a client month went from three days to four hours, not because anyone was let go, but because a qualified specialist stopped keying in details by hand. The time that frees up most often goes into growth: more clients with the same team, without the costs rising alongside.
It’s a fair question, and sometimes doing it yourselves really is the right answer. We say so when the volume doesn’t justify a build: below roughly 300 documents a month the arithmetic usually doesn’t work. The calculator on this site includes running costs, so you can weigh that up before you ever talk to us.
They do change, and that’s exactly what we build for: the model is a replaceable part here, not the foundation. The source of truth is our own database — the document, the counterparty, the entry. The model is attached to the side, and we update it whenever something better appears; for you that’s planned maintenance, not a rebuild.
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