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

Preserves a nested treatment table with the 7-inch, 10-inch, 12-inch, 100-leave-tree, and clearcut columns and the acres/live-lodgepole rows.

✓ Worked🧾 artifact-verifiedinput + output shownTest date not recordedLlamaParse →
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
6893a7fc-87db-41b5-a8fc-06a4f67d61d5
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: "llamaparse",
  scenario: "scanned-research-paper"
})
MCP · mcp.aidemos.com/api/mcp
JSON · ai.aidemos.com/v1/observations/6893a7fc-87db-41b5-a8fc-06a4f67d61d5
Free with attribution.
Same input, same check — 8 other tools
measured on Table Preservation
Adobe API✓ WorkedPreserves a multi-column scientific table of tree treatments and before/after diameters, keeping the treatment rows and inch/cm subcolumns readable.Extend AI✓ WorkedRebuilds multi-row tables with the row/column grid intact, preserving treatment rows and year columns in the scanned table extraction.Landing AI◐ MixedPartially reflects the text that sits between table columns, but the intervening content still disrupts the table structure in the parsed output.Mistral AI✗ FailedBroken column boundaries and disrupted value alignment make the reconstructed table significantly less faithful to the source.Nutrient.io✗ FailedBreaks more complex multi-level tables, with rows and merged cells misaligned or lost once the hierarchy becomes dense.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.Upstage AI◐ MixedKeeps the table values intact but reconstructs the headers incorrectly, leaving a grouped-column table with inconsistent structure.
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