{"observation":{"id":"1dbde32e-95eb-4904-8433-272d8c5e1fdb","tool":"adobe-api","tool_name":"Adobe API","criterion":"table-preservation","criterion_name":"Table Preservation","criterion_definition":"Preserves complex table structures, including rows, columns, multi-row headers, and merged-cell relationships in markdown.","criterion_evidence_type":"transformation","criterion_rank_role":"decisive","criterion_rank_role_reason":"Accurate Markdown conversion of complex PDFs depends on keeping table structure intact, not flattening it into plain text. (3 of 3 judges)","scenario":"scanned-research-paper","scenario_name":"Scanned Research Paper","group_tag":"scanned-research-paper","scenario_description":"An image-only scanned research paper used to stress OCR and layout recovery in a multi-column academic document with figures, charts, tables, captions, and references.","modality":"pdf","input_text":null,"input_artifact_refs":[{"alt":null,"url":"https://d3epheqghktydj.cloudfront.net/convert-a-complex-pdf-into-clean-markdow-scanned-research-pdf-7b86de49784d.pdf","role":"input","filename":"Scanned Research PDF.pdf"}],"stresses":["OCR on scanned pages","Multi-column reading order","Figure and chart handling","Table reconstruction from scans","Caption association","Reference extraction","Overall document structure retention"],"verdict":"worked","score":null,"score_total":null,"note":"Preserves a multi-column scientific table of tree treatments and before/after diameters, keeping the treatment rows and inch/cm subcolumns readable.","evidence_state":"verified","source":null,"artifacts":[{"url":"https://cdn.futuresmart.ai/public/aidemos/57a862fbcd21461ab376ee98f35f965b.png?v=1","role":"input","alt":null},{"url":"https://cdn.futuresmart.ai/public/aidemos/73217e33f9454dd4a51ad4387f6df0de.png?v=1","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://d3epheqghktydj.cloudfront.net/convert-a-complex-pdf-into-clean-markdow-scanned-research-pdf-7b86de49784d.pdf","filename":"Scanned Research PDF.pdf","alt":"Scanned Research Paper","role":"input"}],"modality":"pdf","stresses":["OCR on scanned pages","Multi-column reading order","Figure and chart handling","Table reconstruction from scans","Caption association","Reference extraction","Overall document structure retention"]},"tool_page_slug":"adobe-api","tool_url":"https://aidemos.com/tools/adobe-api","permalink":"https://aidemos.com/evidence/1dbde32e-95eb-4904-8433-272d8c5e1fdb","api_url":"https://ai.aidemos.com/v1/observations/1dbde32e-95eb-4904-8433-272d8c5e1fdb"},"peers":[{"id":"1e354a89-f9a5-4765-af9a-4cbec79fda3e","tool":"extend-ai","tool_name":"Extend AI","verdict":"struggled","score":null,"score_total":null,"note":"Breaks multirow header relationships in a scanned table, so grouped headers and header-level structure are not reliably preserved.","artifact_count":2,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/7e0da44bcebe4ebcb0cc24e9c7092489.png?v=1","evidence_url":"https://aidemos.com/evidence/1e354a89-f9a5-4765-af9a-4cbec79fda3e"},{"id":"6c6cd8b2-a68f-4199-8ad7-e9765bf012f1","tool":"landing-ai","tool_name":"Landing AI","verdict":"worked","score":null,"score_total":null,"note":"Preserves a complex diameter-class table with before-cut, trees-cut-per-acre, and after-cut relationships across the treatment rows and check area.","artifact_count":3,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/56ad045174884d278b8ec196b932b07f.png?v=1","evidence_url":"https://aidemos.com/evidence/6c6cd8b2-a68f-4199-8ad7-e9765bf012f1"},{"id":"c5769b1b-265a-4635-aa20-9c081adcb1d9","tool":"llamaparse","tool_name":"LlamaParse","verdict":"worked","score":null,"score_total":null,"note":"Preserves the harvest-diameter table's rows and aligned columns in the extracted output.","artifact_count":2,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/7139dccb10c2449984babcb6dd5a44a2.png?v=1","evidence_url":"https://aidemos.com/evidence/c5769b1b-265a-4635-aa20-9c081adcb1d9"},{"id":"de43911e-dc72-4aee-a02a-2145d2d7acfb","tool":"mistral-ai","tool_name":"Mistral AI","verdict":"failed","score":null,"score_total":null,"note":"Broken column boundaries and disrupted value alignment make the reconstructed table significantly less faithful to the source.","artifact_count":4,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/56ad045174884d278b8ec196b932b07f.png?v=1","evidence_url":"https://aidemos.com/evidence/de43911e-dc72-4aee-a02a-2145d2d7acfb"},{"id":"97dfdbc2-3390-4bf7-9d20-af8a5dd33d01","tool":"nutrient-io","tool_name":"Nutrient.io","verdict":"worked","score":null,"score_total":null,"note":"Largely preserves grouped-column tables, keeping their internal organization intact in the extracted output.","artifact_count":2,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/57a862fbcd21461ab376ee98f35f965b.png?v=1","evidence_url":"https://aidemos.com/evidence/97dfdbc2-3390-4bf7-9d20-af8a5dd33d01"},{"id":"fcad1a88-bccf-4eea-8bf5-0d8e5dbc22ee","tool":"reducto","tool_name":"Reducto","verdict":"mixed","score":null,"score_total":null,"note":"Partially reconstructs Table 1: most of the roughly 90 numeric values are exact, but literal 0 values in the 12-inch column become blanks, one mean cell picks up stray digits (33.0 830000), and a row-label-only section header is broadcast across all six columns in one instance.","artifact_count":3,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/463058512d444a0796cf3e61494de04e.png?v=1","evidence_url":"https://aidemos.com/evidence/fcad1a88-bccf-4eea-8bf5-0d8e5dbc22ee"},{"id":"c19621dc-83eb-467f-9210-161a2adcac66","tool":"tensorlake","tool_name":"Tensorlake","verdict":"failed","score":null,"score_total":null,"note":"Struggles with hierarchical scanned tables, misplacing column headers and producing unreliable reconstructions on both the multicolumn table and the denser complex table.","artifact_count":6,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/57a862fbcd21461ab376ee98f35f965b.png?v=1","evidence_url":"https://aidemos.com/evidence/c19621dc-83eb-467f-9210-161a2adcac66"},{"id":"6db07c2d-fbc7-464c-ba3c-822a7495c3d5","tool":"upstage-ai","tool_name":"Upstage AI","verdict":"mixed","score":null,"score_total":null,"note":"Keeps the table values intact but reconstructs the headers incorrectly, leaving a grouped-column table with inconsistent structure.","artifact_count":2,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/57a862fbcd21461ab376ee98f35f965b.png?v=1","evidence_url":"https://aidemos.com/evidence/6db07c2d-fbc7-464c-ba3c-822a7495c3d5"}],"other_criteria":[{"id":"32fab15d-0885-4287-94a3-67e0d1d00611","criterion":"complex-document-handling","criterion_name":"Complex Document Handling","rank_role":"decisive","verdict":"struggled","score":null,"score_total":null,"note":"Requires splitting an oversized scanned paper into two PDFs before processing, because the web interface rejects uploads over 1 MB.","artifact_count":6,"evidence_url":"https://aidemos.com/evidence/32fab15d-0885-4287-94a3-67e0d1d00611"},{"id":"24968ab8-597c-4c69-9ec3-a0c216320ebc","criterion":"reading-order-structure","criterion_name":"Reading Order & Structure","rank_role":"decisive","verdict":"failed","score":null,"score_total":null,"note":"Dumps the scanned title page as a dense OCR block without section boundaries or other structural cues, so the document hierarchy is lost.","artifact_count":1,"evidence_url":"https://aidemos.com/evidence/24968ab8-597c-4c69-9ec3-a0c216320ebc"},{"id":"ec57bfbf-d0f3-4011-803c-9f42ea53397b","criterion":"text-ocr-completeness","criterion_name":"Text & OCR Completeness","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"Recovers the visible title, abstract, keywords, and opening paragraphs from a scanned USDA forestry report as dense OCR text.","artifact_count":3,"evidence_url":"https://aidemos.com/evidence/ec57bfbf-d0f3-4011-803c-9f42ea53397b"},{"id":"aaf02083-a041-4bdf-b6af-90778cdde03b","criterion":"visual-content-retention","criterion_name":"Visual Content Retention","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"Keeps chart artwork embedded in the extracted page, placing the residual basal-area figure in situ beneath the extracted table text.","artifact_count":1,"evidence_url":"https://aidemos.com/evidence/aaf02083-a041-4bdf-b6af-90778cdde03b"}],"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":"1e354a89-f9a5-4765-af9a-4cbec79fda3e","tool":"extend-ai","tool_name":"Extend AI","verdict":"struggled","score":null,"score_total":null,"note":"Breaks multirow header relationships in a scanned table, so grouped headers and header-level structure are not reliably preserved."},{"id":"6c6cd8b2-a68f-4199-8ad7-e9765bf012f1","tool":"landing-ai","tool_name":"Landing AI","verdict":"worked","score":null,"score_total":null,"note":"Preserves a complex diameter-class table with before-cut, trees-cut-per-acre, and after-cut relationships across the treatment rows and check area."},{"id":"c5769b1b-265a-4635-aa20-9c081adcb1d9","tool":"llamaparse","tool_name":"LlamaParse","verdict":"worked","score":null,"score_total":null,"note":"Preserves the harvest-diameter table's rows and aligned columns in the extracted output."},{"id":"de43911e-dc72-4aee-a02a-2145d2d7acfb","tool":"mistral-ai","tool_name":"Mistral AI","verdict":"failed","score":null,"score_total":null,"note":"Broken column boundaries and disrupted value alignment make the reconstructed table significantly less faithful to the source."},{"id":"97dfdbc2-3390-4bf7-9d20-af8a5dd33d01","tool":"nutrient-io","tool_name":"Nutrient.io","verdict":"worked","score":null,"score_total":null,"note":"Largely preserves grouped-column tables, keeping their internal organization intact in the extracted output."},{"id":"fcad1a88-bccf-4eea-8bf5-0d8e5dbc22ee","tool":"reducto","tool_name":"Reducto","verdict":"mixed","score":null,"score_total":null,"note":"Partially reconstructs Table 1: most of the roughly 90 numeric values are exact, but literal 0 values in the 12-inch column become blanks, one mean cell picks up stray digits (33.0 830000), and a row-label-only section header is broadcast across all six columns in one instance."},{"id":"c19621dc-83eb-467f-9210-161a2adcac66","tool":"tensorlake","tool_name":"Tensorlake","verdict":"failed","score":null,"score_total":null,"note":"Struggles with hierarchical scanned tables, misplacing column headers and producing unreliable reconstructions on both the multicolumn table and the denser complex table."},{"id":"6db07c2d-fbc7-464c-ba3c-822a7495c3d5","tool":"upstage-ai","tool_name":"Upstage AI","verdict":"mixed","score":null,"score_total":null,"note":"Keeps the table values intact but reconstructs the headers incorrectly, leaving a grouped-column table with inconsistent structure."}]}