{"observation":{"id":"324c753c-f3ab-4165-8bd1-eda961278d78","tool":"tensorlake","tool_name":"Tensorlake","criterion":"advanced-features","criterion_name":"Advanced Features","criterion_definition":"Provides separate table/chart extraction and flags low-confidence OCR or ambiguous regions.","criterion_evidence_type":"transformation","criterion_rank_role":"context","criterion_rank_role_reason":"Separate extraction modes and OCR confidence flags are useful workflow features, but they do not by themselves determine whether the Markdown conversion is good. (3 of 3 judges)","scenario":"hybrid-earnings-report","scenario_name":"Hybrid Earnings Report","group_tag":"hybrid-earnings-report","scenario_description":"A long, real-world hybrid annual report used to benchmark end-to-end PDF-to-markdown conversion. It combines native text, financial tables, charts/graphics, and scanned signature/stamp regions, stressing preservation of document structure, reading order, and embedded visual content across a multi-section report.","modality":"pdf","input_text":null,"input_artifact_refs":[{"alt":null,"url":"https://cdn.futuresmart.ai/public/aidemos/f63a44b441704753b65d1b89dc9b4bbb.pdf?v=1","role":"input","filename":"Target-2015-Annual-Report.pdf"}],"stresses":["Native digital text extraction","Complex financial table preservation","Chart and graphic retention","Image-based signatures and stamps","Reading order across a long multi-section report","Markdown quality and consistency"],"verdict":"worked","score":null,"score_total":null,"note":"Provides separate chart extraction for the SG&A waterfall, outputting chart metadata with a title, axis labels, 10 category labels, and a numeric series instead of only inline prose.","evidence_state":"verified","source":null,"artifacts":[{"url":"https://cdn.futuresmart.ai/public/aidemos/bb341a5637d24cd7b0d5b4c5bb9effb5.png?v=1","role":"input","alt":null},{"url":"https://cdn.futuresmart.ai/public/aidemos/1f04e81ebfcf4659a9500ef5e99a9ac7.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://cdn.futuresmart.ai/public/aidemos/f63a44b441704753b65d1b89dc9b4bbb.pdf?v=1","filename":"Target-2015-Annual-Report.pdf","alt":"Hybrid Earnings Report","role":"input"}],"modality":"pdf","stresses":["Native digital text extraction","Complex financial table preservation","Chart and graphic retention","Image-based signatures and stamps","Reading order across a long multi-section report","Markdown quality and consistency"]},"tool_page_slug":"tensorlake","tool_url":"https://aidemos.com/tools/tensorlake","permalink":"https://aidemos.com/evidence/324c753c-f3ab-4165-8bd1-eda961278d78","api_url":"https://ai.aidemos.com/v1/observations/324c753c-f3ab-4165-8bd1-eda961278d78"},"peers":[{"id":"51f08c65-3c19-4c23-8666-87b5d8a58831","tool":"landing-ai","tool_name":"Landing AI","verdict":"worked","score":null,"score_total":null,"note":"Emits semantic attestation blocks for handwritten-signature regions and a blurry signature stamp, distinguishing the signer/company name and the signature legibility instead of leaving those regions unannotated.","artifact_count":5,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/1f45fe222ffc4719ad527014bd6fabbf.png?v=1","evidence_url":"https://aidemos.com/evidence/51f08c65-3c19-4c23-8666-87b5d8a58831"},{"id":"5b164bff-8ffe-46e2-b493-883b4ed9fed4","tool":"reducto","tool_name":"Reducto","verdict":"worked","score":null,"score_total":null,"note":"The separate schema-driven extract.run endpoint cleanly recovers both a financial table and a donut chart: all requested table rows and all five donut percentages come back exactly.","artifact_count":4,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/27079c195497426b998691e2f7749eea.png?v=1","evidence_url":"https://aidemos.com/evidence/5b164bff-8ffe-46e2-b493-883b4ed9fed4"},{"id":"e260a099-6895-499f-ab5d-82e11a0cf513","tool":"upstage-ai","tool_name":"Upstage AI","verdict":"worked","score":null,"score_total":null,"note":"Separately extracts chart content into textual summaries and value tables, including a waterfall chart and bar charts with year/value pairs and growth statistics.","artifact_count":4,"thumbnail":"https://cdn.futuresmart.ai/public/aidemos/bb341a5637d24cd7b0d5b4c5bb9effb5.png?v=1","evidence_url":"https://aidemos.com/evidence/e260a099-6895-499f-ab5d-82e11a0cf513"}],"other_criteria":[{"id":"b119f634-824d-42b8-8ece-5462ea6b4f0c","criterion":"complex-document-handling","criterion_name":"Complex Document Handling","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"Processes an 84-page mixed-content annual report without collapsing the hierarchy, keeping text, tables, charts, and scanned signatures usable within the extracted workflow.","artifact_count":7,"evidence_url":"https://aidemos.com/evidence/b119f634-824d-42b8-8ece-5462ea6b4f0c"},{"id":"449b0ccc-3d5d-467a-b98b-79653db91504","criterion":"markdown-quality","criterion_name":"Markdown Quality","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"Renders the extraction as structured, copyable markdown in the Document Markdown view rather than a flat text dump.","artifact_count":3,"evidence_url":"https://aidemos.com/evidence/449b0ccc-3d5d-467a-b98b-79653db91504"},{"id":"78afa8fc-60fb-4141-ac60-95e3c6e00369","criterion":"reading-order-structure","criterion_name":"Reading Order & Structure","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"Preserves heading order and section relationships in an 84-page hybrid annual report, keeping the narrative, bullets, and figure placement aligned with the source flow.","artifact_count":3,"evidence_url":"https://aidemos.com/evidence/78afa8fc-60fb-4141-ac60-95e3c6e00369"},{"id":"efc88dd3-8f40-4863-ade4-566f307265b5","criterion":"table-preservation","criterion_name":"Table Preservation","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"Keeps a 5-year financial summary table structured, retaining the row/column relationships across sales, expenses, EBIT, and per-share rows instead of flattening the table.","artifact_count":2,"evidence_url":"https://aidemos.com/evidence/efc88dd3-8f40-4863-ade4-566f307265b5"},{"id":"b3b06de4-1c1f-451a-a26e-d1bb11daed26","criterion":"text-ocr-completeness","criterion_name":"Text & OCR Completeness","rank_role":"decisive","verdict":"mixed","score":null,"score_total":null,"note":"On a blurry Ernst & Young signoff, the OCR preserves the firm reference but makes a symbol-level mistake by rendering the ampersand as '+', so the text is close but not exact.","artifact_count":2,"evidence_url":"https://aidemos.com/evidence/b3b06de4-1c1f-451a-a26e-d1bb11daed26"},{"id":"e528b05b-ad28-4fda-a633-eda580b60c6f","criterion":"visual-content-retention","criterion_name":"Visual Content Retention","rank_role":"decisive","verdict":"worked","score":null,"score_total":null,"note":"Retains scanned signature-page visuals as figure blocks plus signer text, including named executives and dates, rather than dropping the signature regions from the output.","artifact_count":3,"evidence_url":"https://aidemos.com/evidence/e528b05b-ad28-4fda-a633-eda580b60c6f"}],"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":"51f08c65-3c19-4c23-8666-87b5d8a58831","tool":"landing-ai","tool_name":"Landing AI","verdict":"worked","score":null,"score_total":null,"note":"Emits semantic attestation blocks for handwritten-signature regions and a blurry signature stamp, distinguishing the signer/company name and the signature legibility instead of leaving those regions unannotated."},{"id":"5b164bff-8ffe-46e2-b493-883b4ed9fed4","tool":"reducto","tool_name":"Reducto","verdict":"worked","score":null,"score_total":null,"note":"The separate schema-driven extract.run endpoint cleanly recovers both a financial table and a donut chart: all requested table rows and all five donut percentages come back exactly."},{"id":"e260a099-6895-499f-ab5d-82e11a0cf513","tool":"upstage-ai","tool_name":"Upstage AI","verdict":"worked","score":null,"score_total":null,"note":"Separately extracts chart content into textual summaries and value tables, including a waterfall chart and bar charts with year/value pairs and growth statistics."}]}