Evidence · first-party tested/Best AI Tools to Convert Complex PDFs into Clean Markdown with an API

Keeps the table values intact but reconstructs the headers incorrectly, leaving a grouped-column table with inconsistent structure.

◐ Mixed🧾 artifact-verifiedinput + output shownTest date not recordedUpstage AI →
What was measured
Table Preservation

Preserves complex table structures, including rows, columns, multi-row headers, and merged-cell relationships in markdown.

decisive for this rankingtransformation

Accurate Markdown conversion of complex PDFs depends on keeping table structure intact, not flattening it into plain text. (3 of 3 judges)

What was given, what came back

Test input: Scanned Research Paper · pdf · group: scanned-research-paper
Input — what we sent
Input file 1 — as supplied
Input file 1 — as supplied
Input file 2 — as supplied
Scanned Research PDF.pdf
Scanned Research Paper

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.

Why this input is hard
  • · OCR on scanned pages
  • · Multi-column reading order
  • · Figure and chart handling
  • · Table reconstruction from scans
  • · Caption association
  • · Reference extraction
  • · Overall document structure retention
Output — unretouched
image
Provenance
Observation
6db07c2d-fbc7-464c-ba3c-822a7495c3d5
Evidence run
6e3160de-fe46-4b45-b071-72560b5c5d0e
Study
Convert a Complex PDF into Clean Markdown with an API
Research task
86b9h7t37
Tested at
not recorded
Source
first-party
Evidence state
verified
Proof shown
input + output shown
Cost / latency
not captured
Repeat run
not captured
Tester
not captured

The last three rows are honest blanks, not placeholders — our capture has no field for them yet.

Query this
get_evidence({
  tool: "upstage-ai",
  scenario: "scanned-research-paper"
})
MCP · mcp.aidemos.com/api/mcp
JSON · ai.aidemos.com/v1/observations/6db07c2d-fbc7-464c-ba3c-822a7495c3d5
Free with attribution.
Same input, same check — 8 other tools
measured on Table Preservation
Adobe API✗ FailedBreaks a grouped-column table when intervening text appears, fragmenting the 1979–1981 layout and corrupting the extracted alignment.Extend AI⚠ StruggledBreaks multirow header relationships in a scanned table, so grouped headers and header-level structure are not reliably preserved.Landing AI✓ WorkedPreserves a complex diameter-class table with before-cut, trees-cut-per-acre, and after-cut relationships across the treatment rows and check area.LlamaParse✓ WorkedPreserves a nested treatment table with the 7-inch, 10-inch, 12-inch, 100-leave-tree, and clearcut columns and the acres/live-lodgepole rows.Mistral AI✓ WorkedThe multicolumn table is reconstructed without losing its overall layout logic, so the table structure remains readable in the parsed output.Nutrient.io✓ WorkedLargely preserves grouped-column tables, keeping their internal organization intact in the extracted output.Reducto◐ MixedPartially 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.Tensorlake✗ FailedStruggles with hierarchical scanned tables, misplacing column headers and producing unreliable reconstructions on both the multicolumn table and the denser complex table.
This evidence is published in
Best AI Tools to Convert Complex PDFs into Clean Markdown with an API →
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com