Parsebridge
Extract structured Markdown from PDFs with a simple API.
Parsebridge fills a narrow but real need: hosted Docling with zero data retention. If you're building a RAG pipeline and Markdown is all you need, the simple pricing and n8n integration make it a solid choice. The lack of JSON or HTML output limits broader use.
- Developers building RAG pipelines needing PDF-to-Markdown extraction
- Data engineers extracting structured content from PDFs for downstream processing
- Teams needing compliance-friendly document processing with zero data retention
- Organizations using Docling and wanting a hosted, managed API alternative
- Users needing a GUI-based PDF editor or viewer
- Teams that require output formats other than Markdown (JSON, HTML, etc.)
- Users with extremely large PDFs (file size limit of 100MB applies)
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In short
Parsebridge — Extract structured Markdown from PDFs with a simple API. Best for Developers building RAG pipelines needing PDF-to-Markdown extraction, Data engineers extracting structured content from PDFs for downstream processing, Teams needing compliance-friendly document processing with zero data retention. Free to start; paid plans from $17/mo.
What's new in Parsebridge
Checked todayAcross the latest 6 updates: 4 feature updates and 2 news mentions.
Running the Docling API yourself with Docling Serve
How to host Docling REST API with Docling Serve: install, call /v1/convert/source, run async jobs, and production gotchas.
Running Docling in Docker
Production setup for running Docling in Docker: image variants, model cache, GPU passthrough, sizing, and env vars.
Using Docling in n8n to parse PDFs to Markdown
Wire Docling into n8n with Parsebridge community node, parse PDFs from Gmail/Drive/Slack, feed Markdown to Notion/Pinecone/LLM.
Docling vs LlamaParse vs Marker for PDF parsing
Criteria-first comparison of Docling, LlamaParse, and Marker for PDF parsing in RAG: licensing, output, cost per 1k pages, and what to test.
Running Docling on AWS Lambda, Vercel, and serverless platforms
What actually works when running Docling on AWS Lambda or Vercel: hard limits, cold starts, OCR filesystem traps, and production patterns.
Getting started with Docling in Python
Hands-on guide to parsing PDFs with Docling in Python: install, parse first document, handle tables and OCR, and when self-hosting makes sense.
Viability Score
How likely is Parsebridge to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- PDF to Markdown conversion
- Table and layout extraction (merged cells, nested headers, multi-column)
- OCR for scanned pages
- Zero data retention (files deleted immediately after processing)
- Parallel processing engines for speed
- Scale up to 300,000 pages per month
- API key authentication
- Credit-based consumption (1 page = 1 credit)
- Automatic credit refund on processing failure
- Supports URL and file upload endpoints
- Live preview on homepage (page 1 only, no account needed)
- Uses Docling open-source parser
- Image extraction as Markdown comments
- Node.js, Python, PHP, cURL client libraries
- n8n integration
About Parsebridge
Parsebridge is a developer-focused API that converts PDF documents into clean, structured Markdown. Built for teams needing reliable document parsing for RAG pipelines, data extraction, or content migration, it handles complex tables, multi-column layouts, and scanned pages via OCR, outputting Markdown that preserves document structure. The service works by accepting either a PDF URL or an uploaded file, processing it in parallel across multiple parsing engines for speed, and returning Markdown along with metadata like page count and credits used. A key differentiator is zero data retention: files are deleted immediately after processing, making it suitable for compliance-sensitive environments. Parsebridge offers a free trial (50 pages) and paid plans starting at $17/month for 5,000 pages, scaling up to 300,000 pages per month. Under the hood, it uses Docling, an open-source parser known for strong table extraction and layout preservation. For teams already using or evaluating Docling, LlamaParse, or Marker, Parsebridge provides a hosted alternative with a simple API and n8n integration. It is not a general-purpose document conversion tool; it focuses exclusively on PDF-to-Markdown extraction.
Behind the Verdict
Parsebridge is laser-focused: PDF-to-Markdown only, with no distractions. If your pipeline demands Markdown for LLM ingestion and you want to skip self-hosting Docling, this is a clean fit. The zero data retention policy is a genuine differentiator for compliance-heavy workflows — health, legal, finance. Pricing is straightforward and competitive with similar hosted parsers, though the per-page credit model means you pay for every page, even failed ones (though refunds are automatic). The n8n integration is well-documented and practical for automating document flows from email or cloud storage. However, the Markdown-only output is a hard constraint: no JSON, HTML, or raw text options. Also, the 100MB file size limit and lack of image extraction beyond comment references may frustrate some use cases. Compared to LlamaParse, Parsebridge lacks multi-format output but offers a simpler API and better compliance story. We'd reach for it when Markdown is the target and doc retention is a no-go. Pass if you need JSON or HTML output, or if you prefer to self-host to avoid monthly costs.
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Use Cases
- Parse PDF invoices and contracts into Markdown for ingestion into a vector database for RAG.
- Extract tables from research papers for structured data analysis.
- Convert scanned PDFs into clean Markdown for LLM context without retaining files.
- Automate document processing workflows by integrating Parsebridge with n8n.
- Build a document-to-Markdown pipeline that scales to 300,000 pages per month.
Limitations
- File size limits apply (no exact limit published, but large files may be rejected).
- The free preview on the homepage only processes the first page.
- Credits are deducted before processing; if the API key has insufficient credits, a 402 error is returned.
- The service only outputs Markdown, not other formats like JSON or HTML.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Integrations
Resources & Guides
Official links
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Common stack mates teams adopt alongside Parsebridge, with the specific reason each pairing earns its keep.
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