Can Landing AI turn a clean scan into accurate text?
Landing AI produced accurate text for the scanned-document case tested here. The digital invoice and its image-only twin returned the same three values: invoice_number TPH-3301, invoice_date 10 March 2026, and total_due £1,754.40. The twin file is shown with zero extractable characters, and the gap was none. No other test case has a result yet.
1 of 1 test case passed
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The test case
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Image-only twin, same schemaPassEvidence
The tool returned 2 files, shown under Proofs.
{ "data": { "total_due": "£1,754.40", "invoice_date": "10 March 2026", "invoice_number": "TPH-3301" }, "extractionMetadata": { "total_due": { "value": "£1,754.40", "ranges": [ { "start": 1197, "end": 1206 } ] }, "invoice_date": { "value": "10 March 2026", "ranges": [ { "start": 321, "end": 349 } ] }, "invoice_number": { "value": "TPH-3301", "ranges": [ { "start": 295, "end": 320 } ] } }, "extract_id": "extract-01m4an1qjqt6e09jxqvphv5343", "parse_run_id": "parse-01m4an15e5t5xn129hh2rm10ez", "created_at": "2026-10-07T07:43:11.833Z" }
{ "data": { "total_due": "£1,754.40", "invoice_date": "10 March 2026", "invoice_number": "TPH-3301" }, "extractionMetadata": { "total_due": { "value": "£1,754.40", "ranges": [ { "start": 1097, "end": 1106 } ] }, "invoice_date": { "value": "10 March 2026", "ranges": [ { "start": 351, "end": 378 } ] }, "invoice_number": { "value": "TPH-3301", "ranges": [ { "start": 326, "end": 350 } ] } }, "extract_id": "extract-01m4an3y7q61kd7v4hx2es80s9", "parse_run_id": "parse-01m4an2z77xqq6zm44hfg4t8zw", "created_at": "2026-10-07T07:44:24.081Z" }
| ✓ | Expected: Both runs should return the same values, and both results plus the gap should be shown.Found: Both runs returned the same three correct values, and the gap was none. |
The digital invoice and the image-only twin were compared with the same schema. Both produced the same three correct values, and the twin file showed zero extractable characters, so the gap was none.
Different character ranges. The two runs use different source character ranges, which fits the scanned twin being read through OCR rather than an embedded text layer.
Configuration and setup
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How this scenario is graded
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Each test case gets one result per tool: Pass, Fail or Not gradable. A test case we haven't run yet shows Untested. There are no partial results.
- Pass: the tool did everything the test expected, and nothing it said contradicts the correct answer.
- Fail: at least one expected behaviour clearly didn't happen; the row says which and quotes the tool.
- Not gradable: our evidence couldn't settle the outcome (for example a record we needed is missing). It is never counted as a fail, and the row says what's missing.
Where this sits in the benchmark
This page is one cell of a larger study: one tool, one scenario. Only this benchmark's frame appears here.
| Level | Name | Scope |
|---|---|---|
| Benchmark | Structured Document Extraction → | 19 scenarios · 10 tools |
| Capability | OCR → | |
| Scenario | A cleanly scanned document → | |
| Tool | Landing AI → |
Global scenario definition → · Global capability definition → · Landing AI product page →
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