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Layers / Data / RAG / Document parsing

Document parsing

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Turning documents into text a model can read — PDFs, scans, tables, HTML — including OCR and layout recovery. What happens to the passages afterwards is retrieval and search.

19 in this category
SORTED BY STARS · 2 UNMEASURED, GROUPED LAST

NARROW BY WHAT THIS CATEGORY ASKS

LICENCE · 4 NOT READ

OCR · 11 NOT READ

OUTPUT FORMATS · 11 NOT READ

PRODUCTUSED BYSTARSDOWNLOADS 30D
firecrawlPython SDK for the Firecrawl API: web scraping, crawling, web search, and scientific literature search over a research paper index of PubMed, bioRxiv, medRxiv and arXiv abstracts5182,9134,532,052graphifyTurn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing, e120,159paddleocrTurn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.89,363doclingSDK and CLI for parsing PDF, DOCX, HTML, and more, to a unified document representation for powering downstream workflows such as gen AI applications.1567,525LlamaIndexInterface between LLMs and your data1452,118466,012opendataloader-pdfPDF Parser for AI-ready data. Automate PDF accessibility. Open-source.29,336Unstructured.ioA library that prepares raw documents for downstream ML tasks.1215,4134,193,618knowhereKnowhere extracts, parses, and outputs structured chunks ready for AI Agents and RAG.3,175XxerjXERJ is the new way for AI to search data. Its autoindex capability activates agents to know your data without the token waste of grep and sed. One command indexes code, docs, logs and PDFs for search2,525ade-cliThe official CLI for Agentic Document Extraction (ADE) by LandingAI — parse documents and extract schema-shaped data from your terminal2,414NomicNomic Developer API SDK1,880docstrangeExtract and convert data from any document, images, pdfs, word doc, ppt or URL into multiple formats (Markdown, JSON, CSV, HTML) with intelligent structured data extraction and advanced OCR.1,552TurboOCRTurboOCR, >200 img/s OmnidocBench. TensorRT FP16, PP-OCRv6, HTTP + gRPC1,065Hhaiku.ragAgentic RAG for local and self-hosted document search: hybrid retrieval, reranking and multimodal RAG on embedded LanceDB, with Docling parsing and an MCP server606PPOCRLabelPPOCRLabelv3 is a semi-automatic graphic annotation tool suitable for OCR field, with built-in PP-OCR model to automatically detect and re-recognize data.446docling-studioVisual document analysis studio powered by Docling — configure the extraction pipeline, inspect text, tables and bounding boxes in the browser, then chunk, embed and index into OpenSearch and Neo4j.258BbfscanTool for finding URLs, paths, secrets and generating raw HTTP requests and OpenApi specifications from config files and annotations used in JAR / WAR / APK applications.256ReductoReducto: The Agentic Document Platform for AI TeamsVoyage AIEmbedding models and rerankers for retrieval83,800,718

SORTED BY ONE STATED COLUMN · USED BY = LISTED PRODUCTS DEPENDING ON IT, IN THIS DIRECTORY — NOT A POPULARITY FIGURE · NO OVERALL SCORE AND NO RANK COLUMN, BECAUSE BLENDING ADOPTION, STARS AND DOWNLOADS NEEDS WEIGHTS, AND WEIGHTS ARE AN OPINION PRESENTED AS ARITHMETIC

Cite this page

The count and its date sit inside the citation, because “Document parsing” without a date is a claim that quietly goes wrong as the category fills.

infratoapp, “Document parsing — Data / RAG”, read 27 October 2026. 19 listed products. https://www.infratoapp.com/layers/data-rag/parsing

No overall score, and no rank column

Blending adoption, stars and downloads needs weights, and weights are an opinion presented as arithmetic — so this table sorts by one stated column at a time and shows which. This view holds no billing column and joins no billing table: a sponsor cannot appear higher, and the signals meter is a row’s own confidence, never a score you can sort on.

Frequently asked

What is in the Document parsing category?
19 products in the Data / RAG layer of the AI stack. Turning documents into text a model can read — PDFs, scans, tables, HTML — including OCR and layout recovery. What happens to the passages afterwards is retrieval and search. Listed members include firecrawl, graphify and paddleocr. Every fact on each listing carries the page it was read from and the date it was read.
How are Document parsing compared here?
By the 7 attributes this category declares, asked of every member and answered only where a source states it. A product with no answer on record shows a gap rather than a guess, and no blended score is published — weights would be an opinion presented as arithmetic.
firecrawl or graphify?
Both are listed under Document parsing. We publish no verdict between them — we hold no benchmark that would support one. What we do hold is the same attribute sheet for each, side by side with the source behind every value, at /compare/firecrawl-vs-graphify.
What does a blank mean on a document parsing row?
That nobody has told us, not that the answer is no. A hollow ring is "no answer on record", which is a different state from a recorded no — and the two look different on purpose. A listing with a blank has not failed the question; it has not been read for it.
How often are document parsing figures re-read?
Every value carries the date it was read and a link to the page it came from. Prices move fastest and are re-read most often; an attribute read weeks ago says so rather than presenting itself as current. Anything past 21 days is hidden rather than shown stale.
Is this every document parsing there is?
No. This is 19 we have read and can cite. A directory that claimed completeness would be making a promise it cannot keep, so the page states its own count instead and says when a category is too thin to shortlist from.
Can a vendor pay to rank higher here?
No. Nothing on this page can be bought: a sponsor cannot enter a table, reorder a row or change a mark, and there is no ranked position for sale. How the site is paid for, and the line each source of money does not cross, is set out under money and independence at /our-data#sec5.