Read, extract, and reason over the documents that run your business — contracts, statements, forms, and filings — at scale and with an audit trail.
Book a callProcess any document type at volume, with every value traceable back to its source.
Pull fields, tables, and clauses into structured data from any format.
Identify document types and send them where they belong.
Check extracted data against your systems and flag exceptions.
Condense long documents into the parts that matter.
Route low-confidence items to people — and learn from corrections.
Every extraction traces back to its source page.
Why this is harder than it looks.
In a great many businesses the real workflow is not in the software — it is in the contract, the statement, the form, the filing. Those documents arrive in every format anyone has ever invented, and the work of turning them into something a system can act on is done by people, by hand, at a rate that quietly caps how much business you can take on.
A number lifted out of a hundred-page agreement is only useful if you can get back to the page it came from in one click. Every extracted value carries its provenance, so a disagreement about a figure is settled by looking rather than by re-reading the document from the top.
Not every extraction deserves the same trust, and pretending otherwise is how bad data enters a system of record. Low-confidence items are routed to a person before they are relied on, and the corrections that person makes become part of how the system reads the next one.
For most document workloads the valuable answer is not the ninety-five percent that reconciled cleanly — it is the five percent that did not. Validating extracted data against your own systems and surfacing only the mismatches turns a review queue from a pile into a short list.
Each value links to the page it came from.
A complete record of every extraction and decision.
Low-confidence items get a person before they're trusted.
The same three moves on every engagement, whatever the workload.
Forward-deployed engineers sit with your team to learn the real workflows, constraints, and definitions of done.
We stand up intelligence around your systems — scoped, secured, and shaped to your operation from the first build.
What ships keeps improving and stays yours, so the value accrues to your organization over time — not the vendor.
The ones your business actually receives — native PDFs, scans of varying quality, images, office formats, and the structured feeds that sit alongside them. Format range is usually less of a constraint than document variety, which is what the classification step is for.
Accuracy is meaningless as a single number across document types, so we do not quote one. What we do is measure it on your documents during the build, set confidence thresholds accordingly, and route everything below them to a human.
Yes, including tables that span pages and the ones that are really just a grid of text. Tables are also where verification matters most, which is why every extracted cell keeps its link back to the source page.
Into your systems of record, in the shape they expect. Writing back is part of the deployment rather than a separate integration project you inherit afterwards.
A single intelligence layer over your documents, tools, and tribal knowledge — so anyone can get a grounded answer in seconds.
When the off-the-shelf use case doesn't fit, we build an agent around your exact process — integrated with your systems and owned by you.
AI readiness check
A five minute conversation. Honest verdict, including no.
Tap to start. Takes about five minutes.
Describe a piece of work you would want AI doing. We will talk through whether it is deployable yet, and what is missing if it is not. What gets said appears here.
