AI Demos Research — the structured-intelligence platform. Every verdict on these pages opens to the execution behind it.
Graded 7 October 2026

Can Landing AI extract the same field across different layouts?

Landing AI passed this scenario. It returned the correct owed amount from three documents with different layouts: $90.10 from the receipt, $227.33 from the invoice, and USD 157.50 from the other receipt. The screenshots show each value highlighted in the viewer and the same single String field in the schema.

1 of 1 test case passed

Every test case in this scenario has a result.

Pass rate100%1 of 1 with a result
Coverage1 of 1test cases with a result
1PassDid everything it was expected to do.
0FailNo test case failed.
0Not gradableEvery result here could be graded.
0UntestedEvery test case in this scenario has a result.
The pass rate is a summary. The evidence is the test case below: what we sent, what we checked, what the tool returned, and the proof.

The test case

Each test case is judged on its own: Pass, Fail, Not gradable, or Untested. The scenario result above counts this row.

Same field across three layoutsPassEvidence
What we sent
Input 1Document (PDF)
Service receipt with a boxed totals block and a dollar-sign total.
Open the PDF ↗
Input 2Document (PDF)
Invoice with an Amount Due row under a dark-headed table.
Open the PDF ↗
Input 3Document (PDF)
Service receipt with totals written using a USD prefix.
Open the PDF ↗
What the tool returned

The tool returned 3 files, shown under Proofs.

Proof 1Output file (text)
JSON returning "$90.10" for the baseline receipt.
Text7 lines
{
  "data": { "total_amount_owed": "$90.10" },
  "extractionMetadata": { "total_amount_owed": { "value": "$90.10", "ranges": [ { "start": 645, "end": 651 } ] } },
  "extract_id": "extract-01m4any33pf0fpfxaxjjxn1j5x",
  "parse_run_id": "parse-01m4anwjark2xnrs4k0gag21f7",
  "created_at": "2026-10-07T07:58:37.694Z"
}
Open the text file ↗
Proof 2Output file (text)
JSON returning "$227.33" for the invoice.
Text7 lines
{
  "data": { "total_amount_owed": "$227.33" },
  "extractionMetadata": { "total_amount_owed": { "value": "$227.33", "ranges": [ { "start": 666, "end": 673 } ] } },
  "extract_id": "extract-01m4anxd82w9d219gg3n6aex81",
  "parse_run_id": "parse-01m4anwja7gvh9m0wegwbbrpnr",
  "created_at": "2026-10-07T07:58:15.393Z"
}
Open the text file ↗
Proof 3Output file (text)
JSON returning "USD 157.50" for the receipt.
Text7 lines
{
  "data": { "total_amount_owed": "USD 157.50" },
  "extractionMetadata": { "total_amount_owed": { "value": "USD 157.50", "ranges": [ { "start": 643, "end": 653 } ] } },
  "extract_id": "extract-01m4anxqj2qs9bkwd5g2tr1j0g",
  "parse_run_id": "parse-01m4anwja6kn5ww3xjcm7b1svp",
  "created_at": "2026-10-07T07:58:27.116Z"
}
Open the text file ↗
Expected vs. Found
✓Expected: The correct value from each document.Found: Each document's owed amount matched the source: $90.10, $227.33, and USD 157.50; each is highlighted in the viewer.
Supporting proof
Proof 4Screenshot
Screenshot showing the baseline receipt with "$90.10" highlighted.
Open original ↗
Proof 5Screenshot
Screenshot showing the invoice with "$227.33" highlighted.
Open original ↗
Proof 6Screenshot
Screenshot showing the receipt with "USD 157.50" highlighted.
Open original ↗
Why this result

The three source PDFs and the three returned JSON outputs agree on the owed amount for each document, and the screenshots show each value highlighted in the viewer under the same one-field schema.

Also observed on this row

Currency format kept. The product kept each document's own currency format instead of normalizing it. Two results used dollar signs and one used a USD prefix, so a buyer would need to normalize currencies themselves.

Tested by Rugved nichite · evidence dated 7 October 2026

Configuration and setup

How this tool was set up for the run and what the test needed in place. Each row is a fact from the run's records; a fact the records do not hold is left out, not guessed.

Software that produced the output
Landing AI
Build or version
DPT-3 Pro (parse model; app version not exposed)
Surface
Web app
Set up before the run
Three documents of one kind were used: one baseline, one with different label wording and position, and one with another normal layout and value format. The same schema was used throughout.
Extraction field
total_amount_owed
Schema version
v1
Tested
7 October 2026 · Rugved nichite

How this scenario is graded

How we decide Pass, Fail and Not gradable. The same rules apply to every tool tested on this scenario.

How results are decided

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.

The rules
  • 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.

LevelNameScope
BenchmarkStructured Document Extraction →19 scenarios · 10 tools
CapabilityField Extraction →
ScenarioThe same field across layouts →
ToolLanding AI →

History of this result

What has happened to this result since it was first published. Runs and grades are never overwritten: a retest or a re-grade publishes a new result and keeps the earlier one readable.

from the publication record
9 October 2026First publishedStructured Document Extraction v1

Act on this result

Nothing filed here edits the run or the grade. A challenge opens a review, and a review can produce a new run or a re-grade — which becomes the current result and leaves this one in the history.

This matches what I see

You run the same kind of test against your own setup and get the same behaviour.

Agree →
This does not match

Yours behaves differently. Tell us what you got, with a screenshot if you have one.

Disagree →
Point out an issue

Something here is wrong — a reference value, a transcription, a grade.

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Request a retest

On a newer build, a larger dataset, or your own setup.

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We have fixed this

Tell us what changed and we schedule a rerun of the failing test case. The old result stays as history.

Vendor notice →
Filed against this evidenceNothing yet. Challenges, counter-evidence and fix notices appear here with their outcome, and stay on the page after they are resolved.
Cite this result
aidemos.com/benchmarks/structured-document-extraction/results/landing-ai/the-same-field-across-layouts · 1 pass · 0 fail · coverage 1/1 · graded 2026-10-07

The same record is available as structured data through the AI Demos MCP server, with the counts, the coverage and every per-test-case reason carried as fields.

Verify the proof files

These files support this result. Open a file to inspect the original evidence.

Input 1 · Document (PDF) ↗application/pdf · 54 KB
Proof 1 · Output file (text) ↗text/plain; charset=utf-8 · 0 KB
Proof 4 · Screenshot ↗image/png · 117 KB
Input 2 · Document (PDF) ↗application/pdf · 8 KB
Proof 2 · Output file (text) ↗text/plain; charset=utf-8 · 0 KB
Proof 5 · Screenshot ↗image/png · 140 KB
Input 3 · Document (PDF) ↗application/pdf · 7 KB
Proof 3 · Output file (text) ↗text/plain; charset=utf-8 · 0 KB
Proof 6 · Screenshot ↗image/png · 131 KB
File fingerprints (SHA-256)

A fingerprint identifies the exact file used for this result.

Input 1 · Document (PDF)a96bbe1c5b22336e7b54169baf72b85e45eabf1312cd293a1821017b52fa85f7
Proof 1 · Output file (text)0a3bab3267e6c8f6dd64de6cf81e9a3e74b19e74b6d77c2133630f04ce7a8ed1
Proof 4 · Screenshot7d084b2ab111e890c7c4dafc9bb7208fd4c554c0e817e6d28737500b60b37c72
Input 2 · Document (PDF)4a0b1754da9f52ce35a783d58f8e8a1b5e1353b5b992d5553122886f1cd4a638
Proof 2 · Output file (text)dd00769da8b1c9db026c1956ae181590f0405587d3e91c56190c6490b621b939
Proof 5 · Screenshot1e56e06bfe1de905980cc2f78f325851e66cb8e17aaa237ff50dd92de604b155
Input 3 · Document (PDF)0276d246d69482340b53797f4eaa21831977cede22c8c8f14fc48dbf84757660
Proof 3 · Output file (text)24658901e3fbc4f89e1f16dd2240b378e9a6ec51cce8e7654b98e7b2e18bb097
Proof 6 · Screenshot2cd3b3ef31ff118cb3627da7ef50df3b3624b95b05d083fff28f3931a43339ad