Evidence · first-party tested
Reconstructs the bank-statement schema as nested JSON objects rather than flat OCR, populating statement.metadata, account_holder.address, account, branch, statement_period, and balances in the requested hierarchy.
✓ WorkedLanding AI →
A 4-page bank statement PDF with 51 transaction rows, balance-forward continuations, account/branch metadata, rewards information, and disclaimer text. Designed to test end-to-end structured extraction from a dense financial statement.
The observation
Reconstructs the bank-statement schema as nested JSON objects rather than flat OCR, populating statement.metadata, account_holder.address, account, branch, statement_period, and balances in the requested hierarchy.
Criterion: Schema Adherence · Scenario: Bank Statement PDF (group: financial-document-extraction)
Query this
get_evidence({
tool: "landing-ai",
scenario: "financial-document-extraction"
})MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Free with attribution.
Same input, other tools
Real outputs, no retouching · every cell queryable via API & MCP · aidemos.com