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Document intelligence

Documents in. Checked data out.

Read leases, invoices and GRNs into fields a person confirms before your ERP acts.

Colleagues reviewing drawings and documents beside a scanner.

Leases, invoices, purchase orders and GRNs arrive as clean PDFs, as scans and as phone photographs. The system pulls the fields your process runs on and checks them against your master data. A person confirms each one before anything reaches your ERP.

Illustrative example

What this could look like in practice

A retail chain holds leases for several hundred outlets, many of them scans with handwritten riders. The system pulls rent, escalation clause and trigger date, lock-in, renewal notice period and CAM obligations, and puts them beside the scanned page for the leasing manager to confirm. A smudged date gets flagged, not guessed. Rent schedules and renewal alerts then run off the confirmed record, not a spreadsheet.

How the system helps

The work it takes off your team

  • Reads clean PDFs, scans and phone photographs, handwriting included.
  • Checks each field against your vendor, outlet and item master.
  • Flags what it cannot read instead of filling it in.
  • Nothing reaches the ERP until a named person confirms it.

Considerations

Things to settle before building

  • Poor scans and handwriting need an exception queue with an owner.
  • Your ERP stays the record. The extraction is a draft.
  • Alerts must reach the store manager, not a shared inbox.

Outcome measures

Useful things to measure

Suggested yardsticks for judging whether a system like this is earning its place — not results we promise.

  • Documents confirmed without a correction
  • Arrival to confirmed record
  • Missed renewals and obligation dates
  • Invoice and payment rework

Where it applies

Sectors where this fits

Retail and real-estate portfolios · Procurement and accounts payable · Construction tendering, where BOQs and drawings arrive in every format · Regulated operators who must show who approved what