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Document processing

Turn incoming documents into reviewable records

Take the retyping out of invoices, forms and applications, and produce structured records a person can check against the original document.

Who this is for: Anyone saving attachments, renaming files and copying figures into a spreadsheet as a regular part of the week.

Working system available

A working in-house system in this family is available to demonstrate. Its case study shows representative behaviour, safeguards and limitations, together with any measured result and the limits of the run that produced it. No client outcome is claimed.

You will recognise this if…

  • Documents arrive by email and get saved inconsistently, or not at all.
  • The same figures are read off a PDF and typed into a system by hand.
  • Finding the original document behind a spreadsheet row means searching three folders.

What we deliver

  • Invoice and receipt capture
  • Structured field extraction
  • Document classification
  • Naming, filing and records creation
  • Supplier and sender checks
  • Exception and approval queues
  • Recurring finance operations reports
  • Contract, form and application processing
  • Audit trail and reconciliation support

Common builds

Concrete systems in this family, described the same way the free Snapshot describes them.

  • Document processing

    Documents are classified, the useful fields are extracted, and the data lands in the system that needs it.

    A pipeline that reads the documents you already receive, pulls out the fields that matter, checks them against what you expect, and writes them into your finance or records system. Anything it is unsure about is queued for a person rather than guessed.

  • Invoice and finance administration

    Supplier documents read, matched against orders, categorised and posted, with the odd ones flagged.

    An intake pipeline for finance paperwork: extract the figures, match them to what you were expecting, categorise the transaction, push it into your accounting system, and hold anything that does not reconcile for a person.

How we work on this

  1. 01

    Classify first

    A cheap check for what a document is, before an expensive attempt to read it, keeps cost and error down.

  2. 02

    Extract to a schema

    Fields are defined in advance so the output is a record, not a paragraph.

  3. 03

    File traceably

    The source document is stored where the record can point back to it.

  4. 04

    Queue the exceptions

    Unfamiliar senders, missing fields and poor scans surface for review instead of being guessed at.

Systems we connect for this

  • Microsoft 365
  • OneDrive
  • Excel
  • Google Workspace
  • Custom APIs

We connect the systems your team already uses. Naming a platform here means we can integrate with it, not that we are partnered with or endorsed by it.

Evidence

Working in-house systems in this family, shown with representative behaviour, safeguards and limitations.

Questions

Will this approve payments?
No. These workflows prepare records and flag things worth a second look. Approving a payment, verifying that an invoice is genuine and exercising financial judgement stay with your finance team.
What about scanned or photographed documents?
Text PDFs are read directly and scans or photographs use image understanding. Quality varies with the image, which is exactly why poor scans are routed to review rather than extracted optimistically.

Next step

Describe the process that prompted you to read this page. If it is a good fit we will say so, and if it is not we will say that too.