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

Keeps the numeric values in a dense hierarchical table but makes grouped-header semantics less explicit, so parent-child column roles become less clear.

◐ Mixed🧾 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: Financial Report - Table Heavy · pdf · group: financial-report-table-heavy
Input — what we sent
Input file 1 — as supplied
Input file 1 — as supplied
Input file 2 — as supplied
Input file 2 — as supplied
Input file 3 — as supplied
doc.pdf
Financial Report - Table Heavy

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.

Why this input is hard
  • · 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
Output — unretouched
image
Provenance
Observation
f41bfe47-b4b5-4125-aabb-b2f1fe86c857
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: "financial-report-table-heavy"
})
MCP · mcp.aidemos.com/api/mcp
JSON · ai.aidemos.com/v1/observations/f41bfe47-b4b5-4125-aabb-b2f1fe86c857
Free with attribution.
Same input, same check — 8 other tools
measured on Table Preservation
Adobe API✓ WorkedReconstructs the quarterly balance-sheet table with its major asset rows and the two reporting dates, preserving the core balance-sheet layout.Extend AI✓ WorkedPreserves grouped-column structure in the financial tables, including the multilevel segment matrix and the balance-sheet comparison layout.Landing AI◐ MixedRecovers the numeric values from a complex table but merges nested header levels into a single cell, weakening the semantic relationships of the table structure.Mistral AI✗ FailedDistinct header levels are collapsed into a single cell in the multilevel table, weakening the parent-child relationships that define the column semantics.Nutrient.io✗ FailedLoses multi-level header organization in hierarchical tables, so parent-child column relationships are not reconstructed in the markdown output.Reducto✓ WorkedPreserves the balance-sheet hierarchy and values, including Assets > Current assets > Cash and deposits, and also reconstructs the later 9-column segment table with all values correct.Tensorlake✗ FailedBreaks on a more complex multi-header table by losing header hierarchy and omitting at least one header label, producing an incomplete and structurally incorrect reconstruction.Upstage AI✗ FailedMisaligns column headers with data regions in dense financial tables, producing a structurally inconsistent balance-sheet extraction rather than a clean header-to-row mapping.
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