Document AI solutions

Insurance

Make claims-document failures visible.

01

The failure surface

A claims pipeline may ingest photographs of receipts, supporting forms and scanned attachments. A single clean-PDF evaluation does not cover this variation in acquisition quality.

02

What to measure

Use controlled severity cohorts to find where recognition and extraction degrade. Separate document-type coverage from condition coverage so an apparently broad corpus does not mask narrow capture diversity.

03

A scoped evaluation

Agree a scoped set of claims-document classes and the output schema with your team. Retain source grouping, annotation provenance and the model version for reproducible retests.

04

What the evidence supports

Public DocTorture evidence is a synthetic invoice OCR benchmark. Claims-specific accuracy and customer outcomes must be measured in a scoped engagement; they are not inferred from that benchmark.

Build with evidence

See what breaks
before production does.

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