Correctly extracts additional invoice account-details fields, including leaving idb_number blank when the source is blank and capturing product_code as 426 without fabricating values.

✓ Worked🧾 artifact-verifiedinput + output shownTest date not recordedReducto
What was measured
Extraction Accuracy

Are field values correct, complete, and free of OCR or parsing errors, including numerical precision on financial fields?

decisive for this rankingtransformation

Correct field values are the core of the job; wrong or incomplete extraction means the tool failed to retrieve the structured data from the document. (3 of 3 judges)

What was given, what came back

Test input: Invoice PDF · pdf · group: business-document-extraction
Input — what we sent
Invoice PDF.pdf
Invoice PDF

A two-page broadcast advertising invoice PDF with nested header metadata, billing and remit addresses, and eight line items spanning a page break. It was used to stress hierarchical line-item extraction, amount precision, time/day parsing, code extraction, and summary validation.

Why this input is hard
  • · Nested line-item hierarchy extraction
  • · Multi-page continuity across a page break
  • · Precision on large dollar amounts and totals
  • · Parsing complex time slots and day patterns
  • · Extraction of Ad IDs and reconciliation codes
  • · Mapping structured metadata sections correctly
  • · Financial summary validation
  • · Handling political advertising compliance text
Output — unretouched
image
Provenance
Observation
f922a84e-e8ec-4f95-8ae9-0d133a98aa69
Evidence run
a061b9e7-a9c5-443d-a171-b296aaf51b8c
Study
Extract and query structured data from documents using natural language
Research task
86b9y25e5
Tested at
not recorded
Source
first-party
Evidence state
verified
Proof shown
input + output shown
Cost / latency
not captured
Repeat run
not captured
Tester
not captured

The last three rows are honest blanks, not placeholders — our capture has no field for them yet.

Query this
get_evidence({
  tool: "reducto",
  scenario: "business-document-extraction"
})
MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 8 other tools
measured on Extraction Accuracy
Datalab✓ WorkedRecovers invoice metadata and financial totals accurately: invoice number 4064621-1, invoice date 10/28/12, gross total 29750, agency commission 4462.5, net amount due 25287.5, and 8 aired spots match the source.Docsumo✗ FailedThe Advertiser Code field is cross-contaminated with an unrelated field label/value: it should be 155, but the extracted cell shows Net Amount Due instead.Extend AI✗ FailedIt over-reads the payment-term field, outputting `Payment Terms 30 Days` instead of the requested `30 Days`.Landing AI✗ FailedLeaves several station-level fields null—address, city, state, postal_code, main_phone, and billing_phone—even though the station block is present in the schema and related info exists elsewhere in the invoice.LlamaParse✓ WorkedThe invoice totals and headline metadata are extracted consistently: aired_spots is 8, gross_total 29750, agency_commission 4462.5, net_amount_due 25287.5, and payment_terms 30 Days match the source invoice.Nanonets✓ WorkedExtracts invoice and finance values accurately, including invoice number 4064621-1 and summary totals of 8 aired spots, 29750 gross, 4462.5 commission, and 25287.5 net amount due.Retab◐ MixedRetains the source label in payment_terms, returning 'Payment Terms 30 Days' instead of only the requested value, so the field is not fully normalized.Unstract✓ WorkedCaptures the invoice header fields and financial totals exactly, including invoice_number 4064621-1 and the printed gross_total 29,750.00, agency_commission 4,462.50, and net_amount_due 25,287.50.
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com