AI Demos Research — the structured-intelligence platform. Every verdict on these pages opens to the execution behind it.
Graded 26 October 2026

Can FutureSmart Document Intelligence extract repeated records?

FutureSmart Document Intelligence passed this repeated-set case. It returned three line items with the right descriptions, quantities, unit prices, and amounts in the right rows; item code was requested but missing from every record.

1 of 1 test case passed

Every test case in this scenario has a result.

Pass rate100%1 of 1 gradable
Coverage1 of 1test case 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.

Repeated set with correct associationPassEvidence
What we sent
InputDocument (PDF)
PDF input: invoice pages with the goods table and totals
Open the PDF ↗
What the tool returned
JSON
{
  "summary": "This document is an invoice from Harrowgate Industrial Supplies Ltd to Fenwick Water Treatment Ltd for the supply of dosing and chemical-feed equipment. It includes a delivery note confirming the receipt of the items on 18 February 2026.",
  "document_type": "invoice",
  "line_items": [
    {
      "amount": 680,
      "quantity": 2,
      "unit_price": 340,
      "description": "Dosing pump, 240V"
    },
    {
      "amount": 144,
      "quantity": 3,
      "unit_price": 48,
      "description": "Chemical feed tubing, 10m coil"
    },
    {
      "amount": 215,
      "quantity": 1,
      "unit_price": 215,
      "description": "Inline flow sensor"
    }
  ],
  "currency": "GBP",
  "file_name": "invoice_HIS-4402_-_Digital_Scanned_Digital.pdf"
}

JSON output: three line items with matching values

Copied from Output file (JSON), lines 1–26

Open the JSON file ↗
Expected vs. Found
✓Expected: Every record, correct values, correct association; nothing dropped, duplicated, or bound to the wrong record.Found: Three line items were returned, each matching its own row for description, quantity, unit price, and amount; item code was missing from every record.
Supporting proof
Proof 1Screenshot
Document Overview screenshot: three line items and their values
The tool’s response is printed above, under What the tool returned. Show this screenshotOpen original ↗
Why this result

The case passes because the three returned rows match the three line items in value and row position. Item code was requested but missing from every row, and that is a completeness gap rather than an association error.

Also observed on this row

Missing item code. Every returned line item lacked item code.

Image-only page. The second page was image-only and did not affect this repeated-set case; the goods table was on page 3.

Tested by Rugved Nichite · evidence dated 21 September 2026
Limitations of this result

No item code appeared in any line item.

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
FutureSmart Document Intelligence
Build or version
Not exposed by the hosted product
Surface
Web app
Set up before the run
The product was configured in its web app to extract every member of a plainly delimited line-item set with item code, description, quantity, unit price, and amount.
Field setup route
Fields were set up in the product's web app (Settings → Extracted fields), not supplied as JSON.
Line items schema
line_items array with item_code, description, quantity, unit_price, amount
Tested
21 September 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.

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
6 October 2026First publishedStructured Document Extraction v1
21 October 2026Taken down
The page left the site; nothing was deleted.
26 October 2026Republished
27 October 2026Updated — the page was revised
The result is unchanged: 1 pass · 0 fail. The earlier result stays readable. Read the earlier result →

Act on this result

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This matches what I see

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This does not match

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Point out an issue

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Request a retest

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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/futuresmart-document-intelligence/a-repeated-set-of-records · 1 pass · 0 fail · coverage 1/1 · graded 2026-10-26

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.

Proof 1 · Screenshot ↗image/png · 78 KB
Input · Document (PDF) ↗application/pdf · 176 KB
Output file (JSON) ↗application/json · 1 KB
File fingerprints (SHA-256)

A fingerprint identifies the exact file used for this result.

Proof 1 · Screenshot362c4737d5c75916374986695420f65ec89c29edffed089160e08753ef5fdb28
Input · Document (PDF)89fb14d7c0897bbfef47ffa3aa3930ee7eccf62c8a9430710d1906598c9bdfec
Output file (JSON)3b4d2c80f2efe9c029eb21cb5327f8d01a1f192d872ff1e281a30f57d4827485