Document AI solutions

Accounts Payable

Know what survives a difficult invoice upload.

01

The failure surface

Invoices arrive as screenshots, compressed attachments and partial captures. A system can recover most words and still lose a total, due date or supplier identifier that matters to payment processing.

02

What to measure

Stress-test recognition of invoice content, with numeric and date-text retention reported separately. For extraction programs, define the fields, tolerances and matching rules before execution.

03

A scoped evaluation

Build controlled cohorts around capture failures seen in your intake process. Split related source documents together so variants of one invoice do not leak across training and evaluation.

04

What the evidence supports

The retained public benchmark measures OCR recognition, not invoice-parser field accuracy. A custom extraction engagement must establish its own truth schema and field-level acceptance criteria.

Build with evidence

See what breaks
before production does.

Run StressBench against your document model and get a condition-level robustness readout.