{"observation":{"id":"517504c5-f1cc-4741-acfb-c00b4f29897f","tool":"tensorlake","tool_name":"Tensorlake","criterion":"markdown-quality","criterion_name":"Markdown Quality","criterion_definition":"Produces clean, well-structured, usable markdown rather than a flat text dump.","criterion_evidence_type":"transformation","criterion_rank_role":"decisive","criterion_rank_role_reason":"The ranking is specifically about producing clean Markdown, so the quality and usability of the Markdown output directly measures success. (3 of 3 judges)","scenario":"financial-report-table-heavy","scenario_name":"Financial Report - Table Heavy","group_tag":"financial-report-table-heavy","scenario_description":"A table-heavy corporate financial report used to test extraction of dense, hierarchical financial statements with grouped columns, multi-row headers, segment-reporting tables, and narrative disclosures.","modality":"pdf","input_text":null,"input_artifact_refs":[{"alt":null,"url":"https://cdn.futuresmart.ai/public/aidemos/fba42ade5adb4814a3381dd4487a3910.pdf?v=1","role":"input","filename":"doc.pdf"}],"stresses":["Multi-page financial statement extraction","Hierarchical table reconstruction","Grouped columns and multi-row headers","Reading order in a report with mixed narrative and tables","Document structure retention","Markdown usability"],"verdict":"worked","score":null,"score_total":null,"note":"Returns the extraction as structured markdown in the Document Markdown workflow, making the output usable rather than a raw text dump.","evidence_state":"verified","source":null,"artifacts":[{"url":"https://cdn.futuresmart.ai/public/aidemos/4f55f711b11b4124b7d3fdcd08810819.mp4?v=1","role":"context","alt":null},{"url":"https://d3epheqghktydj.cloudfront.net/research-media-tensorlake-financialpdf-output-2f9819c0d2fc.md","role":"output","alt":null}],"run_id":"6e3160de-fe46-4b45-b071-72560b5c5d0e","study_title":"Convert a Complex PDF into Clean Markdown with an API","study_kind":"generation","research_task":"86b9h7t37","tested_at":null,"completeness":"input-and-output","input":{"state":"files","text":null,"files":[{"url":"https://cdn.futuresmart.ai/public/aidemos/fba42ade5adb4814a3381dd4487a3910.pdf?v=1","filename":"doc.pdf","alt":"Financial Report - Table Heavy","role":"input"}],"modality":"pdf","stresses":["Multi-page financial statement extraction","Hierarchical table reconstruction","Grouped columns and multi-row headers","Reading order in a report with mixed narrative and tables","Document structure retention","Markdown usability"]},"tool_page_slug":"tensorlake","tool_url":"https://aidemos.com/tools/tensorlake","permalink":"https://aidemos.com/evidence/517504c5-f1cc-4741-acfb-c00b4f29897f","api_url":"https://ai.aidemos.com/v1/observations/517504c5-f1cc-4741-acfb-c00b4f29897f"},"peers":[{"id":"91c495ea-e42f-469b-8dbf-70720d32cb86","tool":"llamaparse","tool_name":"LlamaParse","verdict":"mixed","score":null,"score_total":null,"note":"Renders the table of contents as sequential text with page numbers instead of a nested TOC structure, so the markdown is usable but flattened.","artifact_count":1,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/8bdf29da12ad4937a62553f452727c1b.png?v=1","evidence_url":"https://aidemos.com/evidence/91c495ea-e42f-469b-8dbf-70720d32cb86"},{"id":"9c7a0e04-472d-43b7-a08c-8cba8763be40","tool":"mistral-ai","tool_name":"Mistral AI","verdict":"worked","score":null,"score_total":null,"note":"The output is organized as a downloadable ZIP containing a consolidated markdown document plus individual page-level files for localized inspection.","artifact_count":3,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/b12d5cd772a647818ad1833789b090d6.pdf?v=1","evidence_url":"https://aidemos.com/evidence/9c7a0e04-472d-43b7-a08c-8cba8763be40"},{"id":"906dd315-1d24-43c4-a4d2-720f7a3c3aa0","tool":"pdf-ai","tool_name":"PDF.ai","verdict":"failed","score":null,"score_total":null,"note":"Markdown export failed on an 18-page table-heavy financial report; the report records \"Output MD: Output failed.\"","artifact_count":2,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/b12d5cd772a647818ad1833789b090d6.pdf?v=1","evidence_url":"https://aidemos.com/evidence/906dd315-1d24-43c4-a4d2-720f7a3c3aa0"},{"id":"aa04c457-96be-40c1-87a5-5813f3f86c31","tool":"reducto","tool_name":"Reducto","verdict":"worked","score":null,"score_total":null,"note":"Keeps the syntax clean: no <signature>, <empty>, <b>, <i>, or <u> tags appear anywhere in the output, and the table-of-contents extract renders as a valid pipe table.","artifact_count":4,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/22ebace50155483ca7780413ab257455.png?v=1","evidence_url":"https://aidemos.com/evidence/aa04c457-96be-40c1-87a5-5813f3f86c31"}],"other_criteria":[{"id":"79747d1f-4b06-48ae-b43f-512e9c2d1465","criterion":"complex-document-handling","criterion_name":"Complex Document Handling","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"Handles a table-heavy 18-page report with numerous tables while keeping the extracted sections aligned to the document flow.","artifact_count":4,"evidence_url":"https://aidemos.com/evidence/79747d1f-4b06-48ae-b43f-512e9c2d1465"},{"id":"9bb6f16e-5cab-4c4b-86e7-adcc09d97654","criterion":"reading-order-structure","criterion_name":"Reading Order & Structure","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"Keeps section ordering and narrative flow in an 18-page table-heavy financial report, preserving the operating-performance section before the tabular disclosures.","artifact_count":2,"evidence_url":"https://aidemos.com/evidence/9bb6f16e-5cab-4c4b-86e7-adcc09d97654"},{"id":"e86e674e-4666-4abc-a7fb-84d1f4bf1ed7","criterion":"table-preservation","criterion_name":"Table Preservation","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"Reconstructs a multilevel segment-results table with grouped previous/present quarter headers, year-over-year change columns, six segment rows, and a total row.","artifact_count":2,"evidence_url":"https://aidemos.com/evidence/e86e674e-4666-4abc-a7fb-84d1f4bf1ed7"},{"id":"63381a32-714a-48c6-b8dc-3ce4fc67279d","criterion":"table-preservation","criterion_name":"Table Preservation","rank_role":"decisive","verdict":"failed","score":null,"score_total":null,"note":"Breaks on a more complex multi-header table by losing header hierarchy and omitting at least one header label, producing an incomplete and structurally incorrect reconstruction.","artifact_count":2,"evidence_url":"https://aidemos.com/evidence/63381a32-714a-48c6-b8dc-3ce4fc67279d"}],"appears_in":[{"page_type":"ranking","slug":"pdf-to-markdown-apis","title":"Best AI Tools to Convert Complex PDFs into Clean Markdown with an API","url":"https://aidemos.com/best/pdf-to-markdown-apis","binding":"run"}],"same_scenario":[{"id":"91c495ea-e42f-469b-8dbf-70720d32cb86","tool":"llamaparse","tool_name":"LlamaParse","verdict":"mixed","score":null,"score_total":null,"note":"Renders the table of contents as sequential text with page numbers instead of a nested TOC structure, so the markdown is usable but flattened."},{"id":"9c7a0e04-472d-43b7-a08c-8cba8763be40","tool":"mistral-ai","tool_name":"Mistral AI","verdict":"worked","score":null,"score_total":null,"note":"The output is organized as a downloadable ZIP containing a consolidated markdown document plus individual page-level files for localized inspection."},{"id":"906dd315-1d24-43c4-a4d2-720f7a3c3aa0","tool":"pdf-ai","tool_name":"PDF.ai","verdict":"failed","score":null,"score_total":null,"note":"Markdown export failed on an 18-page table-heavy financial report; the report records \"Output MD: Output failed.\""},{"id":"aa04c457-96be-40c1-87a5-5813f3f86c31","tool":"reducto","tool_name":"Reducto","verdict":"worked","score":null,"score_total":null,"note":"Keeps the syntax clean: no <signature>, <empty>, <b>, <i>, or <u> tags appear anywhere in the output, and the table-of-contents extract renders as a valid pipe table."}]}