{"observation":{"id":"9c7a0e04-472d-43b7-a08c-8cba8763be40","tool":"mistral-ai","tool_name":"Mistral AI","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":"The output is organized as a downloadable ZIP containing a consolidated markdown document plus individual page-level files for localized inspection.","evidence_state":"verified","source":null,"artifacts":[{"url":"https://cdn.futuresmart.ai/public/aidemos/b12d5cd772a647818ad1833789b090d6.pdf?v=1","role":"input","alt":"b12d5cd772a647818ad1833789b090d6.pdf"},{"url":"https://cdn.futuresmart.ai/public/aidemos/4fe9cad389f14e9fbc8ba68bc8a51dfc.png?v=1","role":"output","alt":null},{"url":"https://d3epheqghktydj.cloudfront.net/research-media-mistral-ai-financial-pdf-output-zip-file-d15fc30bd9c4.zip","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":"mistral-ai","tool_url":"https://aidemos.com/tools/mistral-ai","permalink":"https://aidemos.com/evidence/9c7a0e04-472d-43b7-a08c-8cba8763be40","api_url":"https://ai.aidemos.com/v1/observations/9c7a0e04-472d-43b7-a08c-8cba8763be40"},"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":"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"},{"id":"517504c5-f1cc-4741-acfb-c00b4f29897f","tool":"tensorlake","tool_name":"Tensorlake","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.","artifact_count":2,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/4f55f711b11b4124b7d3fdcd08810819.mp4?v=1","evidence_url":"https://aidemos.com/evidence/517504c5-f1cc-4741-acfb-c00b4f29897f"}],"other_criteria":[{"id":"245a23d8-809d-40ba-9dbf-d685e2c54740","criterion":"complex-document-handling","criterion_name":"Complex Document Handling","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"The tool processes an 18-page table-heavy financial report end-to-end and returns both page-level and consolidated markdown outputs.","artifact_count":4,"evidence_url":"https://aidemos.com/evidence/245a23d8-809d-40ba-9dbf-d685e2c54740"},{"id":"1b28b2b5-cfd9-48db-82e9-11ad35d536f4","criterion":"reading-order-structure","criterion_name":"Reading Order & Structure","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"Document hierarchy and reading flow are preserved across the financial report, with headings staying connected to their explanatory text in the reconstructed output.","artifact_count":2,"evidence_url":"https://aidemos.com/evidence/1b28b2b5-cfd9-48db-82e9-11ad35d536f4"},{"id":"16adbd4c-8e66-485d-9c8a-4c463d4aa966","criterion":"reading-order-structure","criterion_name":"Reading Order & Structure","rank_role":"decisive","verdict":"failed","score":null,"score_total":null,"note":"The table of contents is flattened into raw text, so the original navigational hierarchy is not preserved.","artifact_count":2,"evidence_url":"https://aidemos.com/evidence/16adbd4c-8e66-485d-9c8a-4c463d4aa966"},{"id":"fa59d041-14d6-4e87-b31a-efb38ba1ca3d","criterion":"table-preservation","criterion_name":"Table Preservation","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"The multilevel segment table is preserved with its hierarchical headers intact, maintaining the relationships between the grouped columns and their values.","artifact_count":3,"evidence_url":"https://aidemos.com/evidence/fa59d041-14d6-4e87-b31a-efb38ba1ca3d"},{"id":"5fe802fc-62a5-4a6a-aa9c-9ae77852cde1","criterion":"table-preservation","criterion_name":"Table Preservation","rank_role":"decisive","verdict":"failed","score":null,"score_total":null,"note":"Distinct header levels are collapsed into a single cell in the multilevel table, weakening the parent-child relationships that define the column semantics.","artifact_count":3,"evidence_url":"https://aidemos.com/evidence/5fe802fc-62a5-4a6a-aa9c-9ae77852cde1"}],"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":"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; 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