Best AI APIs to Convert Complex PDFs to Clean Markdown
We tested hosted PDF-to-markdown APIs on the same three hard documents: a long hybrid annual report, a table-heavy financial report, and an image-only scanned research paper. The goal was usable markdown with OCR, tables, charts, and reading order preserved well enough for downstream RAG, search, and reuse.
Excellent for digital-native PDFs with configurable chart extraction; fails on scanned multilevel tables.
#2 Landing AI· #3 LlamaParse· #4 Adobe API· #5 Extend AI· #6 Mistral AI· #7 Upstage AI· #8 Nutrient.io
The ranking
Scores are the average across every check we scored for that tool. Not every tool was scored on every check — the count is shown.
| Tool | Score | Price | Where it lands | ||
|---|---|---|---|---|---|
| #1 | Tensorlake | Usable | 3.6/5 7 checks | — | Strong document structure and table parser, but weak on hierarchical scanned tables |
| #2 | Landing AI | Usable | 3.4/5 7 checks | Free · $1 for 100 credits | Strongest on table reconstruction, but weaker on visual retention and top-level hierarchy. |
| #3 | LlamaParse | Usable | 3.3/5 7 checks | Free · $3/mo | Strong hybrid-document OCR and reading-order reconstruction, but visual assets are largely textified rather than truly retained. |
| #4 | Adobe API | Usable | 3.8/5 7 checks | — | Best at keeping visual assets and financial tables in place; weaker on signatures and hierarchy. |
| #5 | Extend AI | Usable | 3.6/5 7 checks | Free · $500/month | Strong hybrid-document parsing, but visuals often stay out of flow |
| #6 | Mistral AI | Usable | 3.4/5 7 checks | Free · $2 / 1,000 pages | Strong OCR and export automation, with good table recovery but inconsistent hierarchy on longer documents. |
| #7 | Upstage AI | Needs work | 2.7/5 7 checks | Free | Strong at native financial table reconstruction, but weak on scanned multicolumn structure and visual preservation. |
| #8 | Nutrient.io | Unstable | 2.2/5 7 checks | Free · $59/month | Good at basic OCR and section hierarchy, but weak on tables, charts, and other visual content in complex documents. |
What we checked
Every finding below is tied to one of these checks, and to the test that produced it. The number is how many of the 8 tools we recorded findings for.
What we tried
The same 4 tests wererun on every tool. Pick one to see its input and every tool's output.
Tensorlake
Usable#1 of 8Strong document structure and table parser, but weak on hierarchical scanned tables
▸Complex Document Handling4/56 worked well6 findings
Holds up across long mixed-content reports, but quality drops on the most complex scanned tables.
Completes conversion on all three long PDFs tested here—an 84-page hybrid report, an 18-page table-heavy report, and a scanned research paper—and returns markdown exports for each.
Maintains section hierarchy and reading flow across an 84-page hybrid financial report that mixes native text, financial tables, charts, and scanned signatures.
▸Reading Order & Structure4/521 worked well21 findings
Preserves section order and document hierarchy well across long hybrid and scanned documents.
Preserves document hierarchy and heading order so the extracted flow stays close to the source layout.
Keeps the top-down reading order intact across a report section by placing the title, subtitle, figure block, narrative paragraph, and bullet list in one coherent flow instead of flattening them into unordered text.
▸Table Preservation3/514 worked well1 mixed2 struggled12 failed29 findings
Keeps ordinary and multi-section tables mostly intact, but multi-header and hierarchical tables lose headers and relationships.
Fails to reconstruct hierarchical tables reliably on scanned pages, misplacing column headers and producing unstable table structure across multiple examples.
Reconstructs financial tables with row, column, and value relationships intact, keeping the table structure structurally faithful in markdown.
▸Visual Content Retention3/52 worked well1 mixed1 failed4 findings
Extracts chart data and signature content, but visuals are represented as parsed data rather than faithfully retained images in place.
Embedded figures are not retained as visual objects in the markdown output; they are converted into text-only figure descriptions instead of being placed back into the document as images.
Extracts handwritten signature content from scanned pages and preserves it in the parsed output rather than dropping the signature region.
▸Text & OCR Completeness4/53 worked well10 mixed13 findings
Covers scanned signatures and blurry text with few omissions, but complex scanned tables still break down.
Recovers degraded stamp text well enough to capture the Ernst & Young reference, but makes a symbol-level OCR error by rendering the ampersand as a plus sign.
Detects handwritten-signature content from a scanned page and returns it as readable text, including signer names and signature-related annotations.
▸Advanced Features (Bonus)3/516 worked well16 findings
Adds separate chart extraction and signature parsing, but no explicit low-confidence OCR flags are described.
Exposes an API key on the home page and pairs it with documentation support.
Exposes API-key access and documentation from the home page, giving the tool a built-in API entry point alongside the UI workflow.
▸Markdown Quality4/53 worked well3 findings
Outputs usable copyable markdown with clear structure, though it is not a downloadable export.
Produces usable markdown with clear section headings, a figure block, and bullet lists rather than collapsing the report into a flat text dump.
Outputs usable markdown rather than a flat text dump, with section headings, table blocks, chart blocks, and signature text separated into readable markdown structure.
Strongest on table reconstruction, but weaker on visual retention and top-level hierarchy.
▸Complex Document Handling4/54 worked well4 findings
Handles long mixed-content reports consistently, with good results across tables, charts, and scanned pages despite some degradation.
Handles a long 84-page hybrid annual report with tables, charts, and scanned signatures in a fully automated API run, returning a usable markdown export.
Processes an 84-page hybrid report with tables, charts, and scanned signatures in one automated pass, producing usable markdown without manual correction.
▸Reading Order & Structure3/525 worked well1 mixed3 struggled20 failed49 findings
Usually preserves section flow and hierarchy, but major headings and scanned title-page structure are flattened or misread in places.
Misinterprets the title-page hierarchy in a scanned paper, producing an incorrect relationship between the title and surrounding content.
Preserves page flow and local hierarchy in a mixed-content section: the heading, body paragraphs, and intervening content stay in the same logical order across the source and parsed views.
▸Table Preservation4/524 worked well3 mixed2 struggled8 failed37 findings
Reconstructs complex financial and scanned tables well, though nested header semantics and some table text placement are imperfect.
Reconstructs the segment-results table with previous and present first-quarter columns and year-over-year change, covering six segment rows plus the total row.
Flattens nested table headers by collapsing a multi-level header into a single header row, weakening the A-F3 segment grouping even though the numeric body remains readable.
▸Visual Content Retention2/51 worked well6 mixed3 struggled8 failed18 findings
Charts and images are not retained as visual assets; they are mainly converted into text descriptions or annotations.
Does not retain the waterfall chart as a visual asset; it converts the chart into a text description that preserves the numeric values and up/down transitions instead of the original figure.
Does not retain a chart as a visual object; it converts the waterfall chart into text-only bullet descriptions instead of preserving the graphic in place.
▸Text & OCR Completeness4/51 struggled1 finding
Recovers most readable text across hybrid and scanned PDFs, but some scanned title-page and intervening-text OCR errors remain.
Fragments the vertically oriented 'cut completed' note in the table into five OCR pieces ('ed', 'et', 'np', 'cut con', and 'cut'), and the final check-area line is truncated in the extracted text.
▸Advanced Features (Bonus)3/521 worked well21 findings
Includes useful semantic annotations such as attestation/signature handling and chart text extraction, but no clear low-confidence flagging.
The tool exposes developer-facing integration support: the report shows an API key plus documentation with multiple functions, so it can be tested and integrated without manual UI work.
Provides API access plus comprehensive documentation and multiple functions, making the tool straightforward to integrate and test programmatically.
▸Markdown Quality4/52 worked well2 findings
Produces clean, usable markdown output rather than a flat dump, with generally coherent structure.
Returns parsed markdown as a downloadable output through a fully automated API workflow, with no manual correction or post-processing required.
Returns the extraction as downloadable Markdown output across runs, rather than only as an in-app preview.
Strong hybrid-document OCR and reading-order reconstruction, but visual assets are largely textified rather than truly retained.
▸Complex Document Handling4/55 worked well5 findings
Handled long, mixed-content documents well overall, though extraction quality dipped on especially complex table structures.
Handles an 84-page mixed-content annual report end-to-end and returns a usable markdown export without manual correction or post-processing.
Handles an 84-page hybrid annual report end-to-end and returns a usable markdown output without manual correction or post-processing.
▸Reading Order & Structure4/528 worked well3 struggled2 failed33 findings
Kept document hierarchy and column reading flow well across hybrid and scanned layouts, with only partial structure loss in some tables.
Extracts a table of contents as sequential text, recovering entries and page numbers but not the TOC hierarchy or relationships.
Reconstructs scanned multi-column pages into a coherent reading flow, keeping headings aligned with the paragraphs that follow.
▸Table Preservation3/530 worked well4 mixed15 struggled6 failed55 findings
Preserved many table values and some grouped structures, but complex headers and TOC-like structures lost semantic clarity in harder cases.
Reconstructs a multi-level segment table with grouped headers and aligned values, preserving the six segment rows and totals such as 221,102 to 260,250 with a 17.7% Y/Y change.
On a more complex segment table, it preserves the numbers but weakens the grouped-header semantics, making parent-child column roles less explicit in the reconstructed markdown.
▸Visual Content Retention1/54 worked well1 mixed3 struggled12 failed20 findings
Charts, logos, and signatures were converted into text or table summaries instead of being retained as visual assets in the output.
Does not retain embedded visuals as visuals; charts are converted into tables and logo/signature assets are surfaced as text descriptions instead of being preserved in place.
Does not retain charts as charts; it serializes a waterfall chart into a table, changing the visual form in the markdown output.
▸Text & OCR Completeness4/52 worked well2 findings
Recovered most readable text across the hybrid report, financial report, and scanned paper, with only some OCR/recognition imperfections.
Extracts embedded signature text from an image-based signature block, recovering the readable 'Ernst & Young LLP' text from the visual asset.
Recovers blurry signature/stamp text well enough to read the audit-marking as 'signature: Ernst & Young LLP' and keep the page number 32 attached to the extraction.
▸Advanced Features (Bonus)3/516 worked well16 findings
Offered separate handling for tables/charts and downloadable visual assets, but no clear low-confidence or ambiguity flagging was shown.
The interface exposes separate downloadable visual-asset outputs alongside the markdown export, rather than forcing all extracted assets into a single text file.
Provides API-key creation together with documentation support.
▸Markdown Quality4/52 struggled2 findings
Produced usable, structured markdown outputs rather than flat text dumps, with generally clean organization.
Extracts a table of contents as sequential text rather than a structured markdown block, so the entries and page numbers are recovered but the layout hierarchy is lost.
Extracts the table of contents as sequential text rather than a structured TOC, so entries and page numbers are recovered but the TOC’s organization is lost.
Adobe API
Usable#4 of 8Best at keeping visual assets and financial tables in place; weaker on signatures and hierarchy.
▸Complex Document Handling3/52 struggled2 findings
Handles long mixed-content PDFs, but quality drops on split scanned inputs and some structural fidelity degrades in harder documents.
Requires splitting one 12-page scanned paper into two PDF inputs and returns two separate markdown outputs, so the original document is not processed as a single continuous file.
Requires scanned PDFs above 1 MB to be split into separate files before processing, which breaks continuity across the original long document.
▸Reading Order & Structure3/57 worked well14 failed21 findings
Document-level structure is often preserved, but TOC hierarchy, section boundaries, and some scanned-document ordering degrade.
Preserves major section headings and document hierarchy in the 84-page hybrid report, keeping the top-level structure readable in the parsed output.
Preserves document-level hierarchy and major section ordering, keeping headings and narrative sections intact even when paragraph formatting is weaker.
▸Table Preservation4/534 worked well3 mixed3 struggled12 failed52 findings
Preserves most financial table structure היט including grouped columns and balance-sheet layouts, but breaks down on dual headers and tables interrupted by text.
Correctly reconstructs grouped-column tables, keeping headers attached to their corresponding values in the extracted representation.
Preserves compact multi-column table hierarchy and keeps header-value relationships intact in grouped tables.
▸Visual Content Retention5/516 worked well8 failed24 findings
Charts, figures, and images are kept in place and remain visually integrated in the markdown output.
Keeps embedded charts and images integrated in the output layout rather than separating or dropping them, showing strong visual fidelity for mixed-content pages.
Fails to recover handwritten signature imagery, leaving the printed signature block and names but omitting the handwritten marks entirely.
▸Text & OCR Completeness4/51 worked well2 failed3 findings
Generally recovers readable text well, but misses handwritten signatures and shows some OCR/structure gaps on scanned content.
It does not recover handwritten signatures at all; the surrounding printed text remains, but the signature marks disappear from the parsed output.
Fails to recover handwritten signature content while still retaining the surrounding printed text, leaving the signature area incomplete.
Strong hybrid-document parsing, but visuals often stay out of flow
▸Complex Document Handling4/53 worked well3 findings
Handles long mixed-content PDFs well, though quality drops somewhat on the most complex multilevel table layouts.
Can convert an 84-page hybrid annual report with native text, tables, charts, and scanned signatures into a usable downloadable markdown output without manual correction.
Handles an 84-page mixed-content financial report end to end in a single automated markdown export, keeping the converted document usable as a coherent report rather than degrading across sections.
▸Reading Order & Structure4.5/517 worked well17 findings
Keeps section hierarchy and reading flow clear across long reports and scanned papers, with only limited structural drift around complex tables.
Maintains report hierarchy and narrative flow so a section title, paragraph text, and a four-item bullet list stay in readable order instead of collapsing into a flat text dump.
Retains document sections with clear structural organization and consistent flow through a financial report conversion.
▸Table Preservation3.5/513 worked well2 mixed8 struggled4 failed27 findings
Preserves row/column alignment and grouped headers well overall, but multirow and compound headers break in some cases.
Reconstructs a grouped financial table with clear row-and-column alignment and preserves nested header structure in markdown.
Preserves a financial table with a five-column year header (2015, 2014, 2013, 2012 (a), 2011) and aligned line items, keeping row-column correspondence intact.
▸Visual Content Retention3/55 worked well10 mixed3 struggled18 findings
Charts and logos are retained as captions or references, but they are not consistently kept inline with the document flow.
Preserves a visual asset as a separate structured reference rather than keeping it inline with surrounding text, so the image is retained but out of document context.
Extracts chart values but does not fully retain the chart's visual trend structure, so data is captured more faithfully than the visualization.
▸Text & OCR Completeness4.5/52 worked well6 mixed3 struggled11 findings
Covers native text, scanned pages, signatures, handwriting, and low-clarity stamps with only minor OCR slips and a few missing contextual bits.
Drops annotations positioned between table columns, losing contextual text that should have been captured with the table.
Correctly extracts signature blocks and a blurred stamp, but can misread low-clarity text by turning "LLP" into "1LP".
▸Advanced Features (Bonus)2/514 worked well14 findings
Shows structured table/chart extraction, but there is no clear evidence of explicit low-confidence OCR or ambiguity flagging.
Provides API-key provisioning from the developers tab together with documentation support, indicating productized API access rather than a one-off demo path.
Exposes API-key generation in the developer area alongside documentation support, enabling programmatic use without manual post-processing.
Strong OCR and export automation, with good table recovery but inconsistent hierarchy on longer documents.
▸Complex Document Handling3/55 worked well1 mixed6 findings
Processed long mixed-content PDFs end-to-end, but quality degraded on hierarchy and complex table reconstruction in larger documents.
Handles an 84-page mixed-content report across most sections without full collapse, but hierarchy becomes flattened in some places, so long-document consistency is only partial.
Keeps reading flow intact on page 6 of an 18-page report, preserving the section heading and paragraph order inside a dense narrative block.
▸Reading Order & Structure3/519 worked well1 mixed4 struggled16 failed40 findings
Reading flow was often preserved, but hierarchy was inconsistent, with flattened TOCs and missed section levels.
Recovers the opening content but flattens the structural hierarchy, losing the semantic distinction between the title and the abstract.
The scanned paper is reconstructed with section hierarchy and reading flow intact, so headings and supporting paragraphs stay correctly connected despite the multi-column layout.
▸Table Preservation3/522 worked well1 mixed2 struggled15 failed40 findings
Handled some layered financial tables well, but multilevel headers and complex scanned tables lost structural fidelity.
Preserves the hierarchical header structure in dense financial tables, keeping parent headers and their child columns related in the reconstructed markdown.
The parser breaks column boundaries and disrupts value alignment in a complex table, making the reconstructed table materially less faithful to the source.
▸Visual Content Retention4/515 worked well15 findings
Charts, signatures, and other visuals were retained as page-linked assets in the output folders rather than being dropped.
It extracts visual assets into page-specific folders and keeps charts, signatures, and other elements associated with their source pages rather than collapsing them into one combined output.
Exports charts, signatures, and other visual assets into page-specific folders so they remain associated with their source pages instead of being collapsed into a single output blob.
▸Markdown Quality4/55 worked well5 findings
Exported usable overall and page-wise Markdown files in downloadable ZIPs, though structure could flatten in places.
Exports a usable markdown package with both consolidated and page-wise files inside a downloadable ZIP, supporting end-to-end consumption and page-level validation without manual post-processing.
The tool returns usable markdown in a downloadable ZIP that includes both a consolidated document and page-wise markdown files, supporting both end-to-end consumption and page-level inspection.
Strong at native financial table reconstruction, but weak on scanned multicolumn structure and visual preservation.
▸Complex Document Handling3/51 worked well1 finding
Handles long hybrid reports end-to-end, but quality drops on mixed-content layouts such as signatures, multicolumn text, and scanned pages.
Accepts an 84-page hybrid annual report and returns a downloadable markdown file through a fully automated API call, with no manual correction or post-processing required.
▸Reading Order & Structure2/57 worked well25 failed32 findings
Hierarchy works in parts, but multicolumn and scanned documents lose paragraph order and section structure.
Flattens a section heading into body text, removing the visual and structural distinction between the heading and the content it introduces.
Loses the reading order on a dense scanned two-column page, flattening the document flow so the original section sequencing is not maintained.
▸Table Preservation3/54 worked well12 mixed4 struggled7 failed27 findings
Reconstructs native financial tables well, but complex headers and some table layouts become misaligned in other documents.
Preserves financial table rows, columns, and value placement with strong fidelity, but misses a small number of currency symbols, leaving the numeric rendering slightly incomplete.
Reconstructs a five-year financial table with correct row/value placement, but misses a small number of currency symbols in the extracted cells.
▸Visual Content Retention2/53 mixed4 struggled12 failed19 findings
Charts and figures are converted into text/value extraction rather than preserved as visual assets in the right position.
Fails to preserve signature-page visuals: handwritten signatures are not clearly identified and the surrounding section structure collapses during extraction.
Does not reliably detect or identify handwritten signatures, so the signature block is not retained as legible visual content even though nearby digital text is recovered.
▸Text & OCR Completeness4/52 mixed1 struggled3 findings
Covers most readable content and handles scanned pages, but some currency symbols and structural details are missed.
Extracts most table values correctly, but misses a small number of currency symbols, so the OCR is not fully complete for numeric notation.
Preserves the numeric amounts in the same 11-row table, but drops the currency symbols on most extracted values, so the OCR is not fully complete.
▸Advanced Features (Bonus)2/53 worked well3 mixed6 findings
Provides chart/table extraction and API automation, but does not clearly flag low-confidence OCR or ambiguous regions.
Provides documented API-key access for endpoint use.
Recovers chart values and tags the asset, but emits them as raw delimiter-separated text instead of an organized chart representation.
Good at basic OCR and section hierarchy, but weak on tables, charts, and other visual content in complex documents.
▸Complex Document Handling2/51 mixed2 failed3 findings
The tool processed long, mixed-content PDFs, but quality degraded on complex tables, chart pages, and scanned layouts.
As table complexity increases to multi-level grouped rows and column hierarchies, the parser loses the ability to preserve structural boundaries, with cells misaligned, merged incorrectly, or lost entirely.
Recovers some section/body hierarchy in isolated parts of an 18-page filing, but only selectively rather than consistently across the document.
▸Reading Order & Structure3/518 worked well4 struggled10 failed32 findings
Section hierarchy was preserved in some places, but paragraph flow and page-level order broke in scanned and dense documents.
Struggles with paragraph ordering in a table-heavy financial report: paragraph boundaries fragment, and the narrative flow is not consistently preserved.
Preserves hierarchical reading order in a scanned research paper, correctly aligning section headings with the corresponding column content.
▸Table Preservation2/57 worked well7 struggled16 failed30 findings
Simple and grouped tables were sometimes usable, but multi-level headers and complex row/column relationships were often misaligned or lost.
Breaks a straightforward financial table into misaligned rows and columns, weakening the row-to-value relationships and losing the source table’s structure in markdown.
Breaks down on a more complex grouped-row table, with cell boundaries misaligned, merged incorrectly, or lost.
▸Visual Content Retention1/57 mixed7 struggled13 failed27 findings
Chart values were extracted in linear form, but figures, chart semantics, and handwritten signatures were not retained as visual content.
Extracts chart values from a scanned figure but does not retain the chart’s structure, axes, or layout relationships.
The tool keeps the surrounding signature-related text but omits the handwritten signature itself, so the visual signature content is not retained in the output.
▸Markdown Quality3/51 worked well1 finding
Outputs were delivered as usable markdown, but structural issues and fragmented content reduced overall markdown cleanliness.
Returns the extraction as a downloadable Markdown file, providing a usable markdown output format for the parsed report.
Final Take
Overall, Extend AI is the best balanced pick from these scorecards. It has the strongest markdown quality (5/5), very strong reading-order structure (4.5/5), strong OCR (4.5/5), and solid complex-document handling (4/5). The main trade-off is that visual-content-retention is only mid-pack (3/5), so it is not the best option when preserving page layout and visual assets is the priority. If layout fidelity matters most, Adobe API wins that lane: it has the best visual-content-retention (5/5) and strong table preservation (4/5), with good OCR (4/5) and markdown quality (4/5). Its weaker point is hierarchy/signature handling, so it is better for visually faithful extraction than for clean semantic structure. For table-heavy documents, Landing AI is one of the top choices with table-preservation at 4/5 and solid OCR/markdown (4/5 each), but its visual retention is very weak (1/5) and reading order is only moderate (3/5). LlamaParse and Tensorlake are better if you care more about structure and reading order in mixed PDFs: both reach 4/5 on reading order, and LlamaParse is specifically strong on mixed PDFs, though it loses more on visual retention. Tensorlake is the more structured of the two, but it is still weaker on hierarchical scanned tables. Mistral AI is the best compromise when you want good OCR, better visual retention than most competitors, and export automation, but its hierarchy gets less consistent on longer documents. Upstage AI is a niche pick for native financial table reconstruction, while PDF Vector and PDF.ai are not competitive here, with PDF.ai failing outright.
Similar Tools
The tools we tested for this use case — each card opens its full tested review.
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