{"observation":{"id":"310a731e-d9ba-4ab5-9782-fb4b8d4dabdb","tool":"extend-ai","tool_name":"Extend AI","criterion":"extraction-accuracy","criterion_name":"Extraction Accuracy","criterion_definition":"Are field values correct, complete, and free of OCR or parsing errors, including numerical precision on financial fields?","criterion_evidence_type":"transformation","criterion_rank_role":"decisive","criterion_rank_role_reason":"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)","scenario":"bank-statement-pdf","scenario_name":"Bank Statement PDF","group_tag":"business-document-extraction","scenario_description":"A four-page bank statement PDF with dense transaction tables, balance-forward bridges, account metadata, rewards data, and disclaimer text. It was used to stress schema-driven extraction, multi-page continuity, row completeness, and financial numerical accuracy.","modality":"pdf","input_text":null,"input_artifact_refs":[{"alt":null,"url":"https://cdn.futuresmart.ai/public/aidemos/a459a9de9c8a466d8f69b112e04ddad2.pdf?v=1","role":"input","filename":"Bank Statement PDF.pdf"}],"stresses":["Table extraction across 50+ transaction rows","Multi-page continuity with balance-forward bridges","Parsing structured account metadata alongside unstructured transaction descriptions","Numerical accuracy for deposits, withdrawals, running balances, and summaries","Extraction of nested rewards and disclaimer sections"],"verdict":"failed","score":null,"score_total":null,"note":"The summary aggregation is incorrect: `total_transactions` is 49 in the output, while the report says the expected count after exclusions is 40.","evidence_state":"verified","source":null,"artifacts":[{"url":"https://d3epheqghktydj.cloudfront.net/research-media-bank-statement-2-jul-a511cf7bd0d6.png","role":"input","alt":"Research media bank statement 2 jul.png"},{"url":"https://d3epheqghktydj.cloudfront.net/research-media-extend-ai-bank-statement-summary-a4a38bf7978f.png","role":"output","alt":null}],"run_id":"a061b9e7-a9c5-443d-a171-b296aaf51b8c","study_title":"Extract and query structured data from documents using natural language","study_kind":"generation","research_task":"86b9y25e5","tested_at":null,"completeness":"input-and-output","input":{"state":"files","text":null,"files":[{"url":"https://cdn.futuresmart.ai/public/aidemos/a459a9de9c8a466d8f69b112e04ddad2.pdf?v=1","filename":"Bank Statement PDF.pdf","alt":"Bank Statement PDF","role":"input"}],"modality":"pdf","stresses":["Table extraction across 50+ transaction rows","Multi-page continuity with balance-forward bridges","Parsing structured account metadata alongside unstructured transaction descriptions","Numerical accuracy for deposits, withdrawals, running balances, and summaries","Extraction of nested rewards and disclaimer sections"]},"tool_page_slug":"extend-ai","tool_url":"https://aidemos.com/tools/extend-ai","permalink":"https://aidemos.com/evidence/310a731e-d9ba-4ab5-9782-fb4b8d4dabdb","api_url":"https://ai.aidemos.com/v1/observations/310a731e-d9ba-4ab5-9782-fb4b8d4dabdb"},"peers":[{"id":"3f57949b-b930-488c-9c76-b9ebc3b73d51","tool":"datalab","tool_name":"Datalab","verdict":"struggled","score":null,"score_total":null,"note":"Misplaces a bank-statement transaction across dates: a row that belongs to 18 Jun is attached to the 19 Jun record after merging, so date association is unreliable.","artifact_count":2,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/80135a758c5a4d2aa2187e8af3f050e8.png?v=1","evidence_url":"https://aidemos.com/evidence/3f57949b-b930-488c-9c76-b9ebc3b73d51"},{"id":"b2117cc5-be67-41db-95df-70412d9cd338","tool":"docsumo","tool_name":"Docsumo","verdict":"mixed","score":null,"score_total":null,"note":"In the rewards scheme table, zero-value cells render as blank rather than as 0, so the extractor preserves the row structure but loses explicit zero values.","artifact_count":1,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/7226096bd0504b8281df59d043c812b5.png?v=1","evidence_url":"https://aidemos.com/evidence/b2117cc5-be67-41db-95df-70412d9cd338"},{"id":"5efe531d-6c34-4551-88f5-d36447fed696","tool":"landing-ai","tool_name":"Landing AI","verdict":"worked","score":null,"score_total":null,"note":"Preserves statement metadata and balances with exact values, including bank_name \"Standard Chartered\", statement_date \"16 Jul 2019\", currency \"INR\", opening_balance 114453.65, and closing_balance 116149.46.","artifact_count":3,"thumbnail":"https://d3epheqghktydj.cloudfront.net/research-media-bank-statement-2-jul-a511cf7bd0d6.png","evidence_url":"https://aidemos.com/evidence/5efe531d-6c34-4551-88f5-d36447fed696"},{"id":"a2fd0afa-58a4-4290-92a6-9396e7807f89","tool":"llamaparse","tool_name":"LlamaParse","verdict":"struggled","score":null,"score_total":null,"note":"The tool leaves value_date blank on some bank transactions even though the source statement contains value dates, so transaction metadata is only partially accurate.","artifact_count":1,"thumbnail":"https://d3epheqghktydj.cloudfront.net/research-media-llamaparse-bank-statement-16-jul-value-d-4906fee56b7b.png","evidence_url":"https://aidemos.com/evidence/a2fd0afa-58a4-4290-92a6-9396e7807f89"},{"id":"0102a587-271f-42b7-8426-de7037082e4b","tool":"nanonets","tool_name":"Nanonets","verdict":"worked","score":null,"score_total":null,"note":"Correctly extracts high-level statement values, including account number 42710540422 and total deposits 70986.83, rather than corrupting the header fields.","artifact_count":4,"thumbnail":"https://d3epheqghktydj.cloudfront.net/research-media-bank-statement-2-jul-a511cf7bd0d6.png","evidence_url":"https://aidemos.com/evidence/0102a587-271f-42b7-8426-de7037082e4b"},{"id":"07a518db-9ca5-4d73-b004-716f8b27d2c3","tool":"reducto","tool_name":"Reducto","verdict":"worked","score":null,"score_total":null,"note":"Correctly extracts the account-holder/customer name from the bank statement and attaches a citation bounding box to the source text.","artifact_count":1,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/ea57eeef1c344aa5b83bada650c0ab88.png?v=1","evidence_url":"https://aidemos.com/evidence/07a518db-9ca5-4d73-b004-716f8b27d2c3"},{"id":"0f4fd75a-64e5-484e-b542-9c63073b0692","tool":"retab","tool_name":"Retab","verdict":"worked","score":null,"score_total":null,"note":"Docsumo extracts the bank statement into structured customer, branch, and summary fields, including the account holder name, address, totals, and closing balance, and also supports QA over the document.","artifact_count":0,"thumbnail":null,"evidence_url":"https://aidemos.com/evidence/0f4fd75a-64e5-484e-b542-9c63073b0692"},{"id":"d859ffe7-484f-444c-adcf-a0fe358bcced","tool":"unstract","tool_name":"Unstract","verdict":"failed","score":null,"score_total":null,"note":"Understates the derived bank-summary count: summary.total_transactions is reported as 43 even though the PDF contains 51 transactions, a 16% undercount.","artifact_count":3,"thumbnail":"https://d3epheqghktydj.cloudfront.net/research-media-bank-statement-2-jul-a511cf7bd0d6.png","evidence_url":"https://aidemos.com/evidence/d859ffe7-484f-444c-adcf-a0fe358bcced"}],"other_criteria":[{"id":"b1ccd11a-19d7-4af9-93c2-1ba1086296e5","criterion":"schema-adherence","criterion_name":"Schema Adherence","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"The tool reconstructs the bank-statement hierarchy into nested JSON with branch, account, rewards, metadata, balances, summary, and transaction-related objects present in the requested layout.","artifact_count":5,"evidence_url":"https://aidemos.com/evidence/b1ccd11a-19d7-4af9-93c2-1ba1086296e5"},{"id":"ca67652c-8a96-456d-92ef-c2817c381589","criterion":"semantic-field-enrichment","criterion_name":"Semantic Field Enrichment","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"The tool infers transaction direction from free text, classifying an ATM entry as `Withdrawal` and populating `withdrawal_amount: 1000`.","artifact_count":2,"evidence_url":"https://aidemos.com/evidence/ca67652c-8a96-456d-92ef-c2817c381589"},{"id":"2c08bc5e-efaf-45c1-91d9-08a43c075910","criterion":"semantic-field-enrichment","criterion_name":"Semantic Field Enrichment","rank_role":"decisive","verdict":"failed","score":null,"score_total":null,"note":"It leaves `transaction_id` null even when the description contains embedded reference numbers, so identifier extraction is not recovered from the transaction text.","artifact_count":1,"evidence_url":"https://aidemos.com/evidence/2c08bc5e-efaf-45c1-91d9-08a43c075910"},{"id":"010e7dbd-9574-4e0f-bdc3-c370101d3914","criterion":"structural-clean-output","criterion_name":"Structural Clean Output","rank_role":"context","verdict":"failed","score":null,"score_total":null,"note":"The output reorders top-level schema objects instead of preserving the declared sequence, so consumers that depend on the original order need an extra transformation step.","artifact_count":1,"evidence_url":"https://aidemos.com/evidence/010e7dbd-9574-4e0f-bdc3-c370101d3914"}],"appears_in":[{"page_type":"ranking","slug":"document-extraction","title":"Best AI Tools for Extracting Structured Data from Business Documents","url":"https://aidemos.com/best/document-extraction","binding":"run"},{"page_type":"tool","slug":"docsumo","title":null,"url":"https://aidemos.com/tools/docsumo","binding":"run"}],"same_scenario":[{"id":"3f57949b-b930-488c-9c76-b9ebc3b73d51","tool":"datalab","tool_name":"Datalab","verdict":"struggled","score":null,"score_total":null,"note":"Misplaces a bank-statement transaction across dates: a row that belongs to 18 Jun is attached to the 19 Jun record after merging, so date association is unreliable."},{"id":"b2117cc5-be67-41db-95df-70412d9cd338","tool":"docsumo","tool_name":"Docsumo","verdict":"mixed","score":null,"score_total":null,"note":"In the rewards scheme table, zero-value cells render as blank rather than as 0, so the extractor preserves the row structure but loses explicit zero values."},{"id":"5efe531d-6c34-4551-88f5-d36447fed696","tool":"landing-ai","tool_name":"Landing AI","verdict":"worked","score":null,"score_total":null,"note":"Preserves statement metadata and balances with exact values, including bank_name \"Standard Chartered\", statement_date \"16 Jul 2019\", currency \"INR\", opening_balance 114453.65, and closing_balance 116149.46."},{"id":"a2fd0afa-58a4-4290-92a6-9396e7807f89","tool":"llamaparse","tool_name":"LlamaParse","verdict":"struggled","score":null,"score_total":null,"note":"The tool leaves value_date blank on some bank transactions even though the source statement contains value dates, so transaction metadata is only partially accurate."},{"id":"0102a587-271f-42b7-8426-de7037082e4b","tool":"nanonets","tool_name":"Nanonets","verdict":"worked","score":null,"score_total":null,"note":"Correctly extracts high-level statement values, including account number 42710540422 and total deposits 70986.83, rather than corrupting the header fields."},{"id":"07a518db-9ca5-4d73-b004-716f8b27d2c3","tool":"reducto","tool_name":"Reducto","verdict":"worked","score":null,"score_total":null,"note":"Correctly extracts the account-holder/customer name from the bank statement and attaches a citation bounding box to the source text."},{"id":"0f4fd75a-64e5-484e-b542-9c63073b0692","tool":"retab","tool_name":"Retab","verdict":"worked","score":null,"score_total":null,"note":"Docsumo extracts the bank statement into structured customer, branch, and summary fields, including the account holder name, address, totals, and closing balance, and also supports QA over the document."},{"id":"d859ffe7-484f-444c-adcf-a0fe358bcced","tool":"unstract","tool_name":"Unstract","verdict":"failed","score":null,"score_total":null,"note":"Understates the derived bank-summary count: summary.total_transactions is reported as 43 even though the PDF contains 51 transactions, a 16% undercount."}]}