Products · Parse
Any document. Clean Markdown. Instantly.
ParseAI Parse converts any document into clean, structured markdown via a single API call. Zero data retention. Built for AI pipelines and LLM applications.
Request
POST /v1/parse
Content-Type: application/json
{
"document": "base64_or_url",
"output_format": "markdown"
}
Response
# Invoice
**Vendor:** Acme Corp Ltd
**Date:** 12 Apr 2026
| Item | Qty | Amount |
|------|-----|--------|
| Service A | 1 | 47,295 |
Markdown Output
Headers, tables, lists and paragraphs preserved. Ready for any LLM.
Zero Data Retention
Documents processed on the fly. Nothing stored, nothing logged.
Any Format
PDFs, scans, mobile photos, mixed languages. One endpoint, all formats.
Output
Not just text. Structured, hierarchical markdown.
Most document tools extract raw text and discard the structure. Parse preserves it. When a document has a heading, the output has a # header. When it has a data table, the output has a markdown table with aligned columns. When it has a bullet list, the output has a list. The structure is faithful to the original, which is exactly what LLMs need to reason accurately about document content.
# Tax Invoice
**Invoice No:** INV-2026-0042
**Date:** 12 April 2026
| Description | Qty | Rate | Amount |
|-------------|-----|------|--------|
| Consulting Services | 1 | 40,000 | 40,000 |
| Cloud Setup | 3 | 2,500 | 7,500 |
**Subtotal:** 47,500
**GST (18%):** 8,550
**Total:** 56,050
Process
One request. Clean output.
Submit any document
POST your document to the Parse endpoint as a base64 string or URL. Supported formats include PDF, PNG, JPG, TIFF, and WEBP. Multi-page documents up to 50 pages are processed in a single request.
ParseAI reads the structure
The model reads the document as a human would, understanding layout, hierarchy, headings, tables, and relationships between elements. It does not perform simple character recognition. It understands the document semantically.
Receive clean markdown
The API response contains the full document as structured markdown. The document is never stored. The entire process is ephemeral: nothing written to disk, nothing logged, nothing retained.
Applications
What teams build with Parse
RAG Knowledge Bases
Parse converts documents into clean markdown that vector databases can chunk and index correctly. Document headings become natural chunk boundaries. Tables remain structured. The retrieval quality of your RAG system depends directly on the quality of document parsing. Parse gets this right.
LLM Context Injection
Feed parsed documents directly into LLM prompts. Structured markdown helps models reason more accurately than raw text dumps. Headers provide navigation context, tables preserve relationships, and bold labels highlight key fields. Token efficiency improves when structure is preserved.
Document Chat Applications
Build Q&A interfaces over document collections. Parse handles the preprocessing step automatically, converting uploaded documents into the structured format your application needs. Works with any LLM framework including LangChain, LlamaIndex, and custom pipelines.
AI Agent Memory
Give agents structured access to document content. When an agent needs to reason about an invoice, a contract, or a medical report, Parse provides the structured representation the agent needs, without requiring the agent to understand raw PDF internals.
Zero retention. By design.
Zero retention is not a feature added later. It is how Parse is architected. Documents are processed in memory and the markdown output is returned in the same API response. Nothing is written to disk. Nothing is logged. No content is used for model training. No data is retained after the response is sent.
This makes Parse suitable for sensitive document categories: financial records, medical reports, legal agreements, identity documents, and any content that cannot leave your control.
0 bytes stored
Documents are never written to disk
0 ms retention
Processed and discarded in the same request
No training
Your documents are never used for model improvement
FAQ
Common questions
What document formats does Parse support?
Parse accepts PDF, PNG, JPG, TIFF, and WEBP files. You can submit the document as a base64-encoded string or as a publicly accessible URL. Multi-page documents are fully supported up to 50 pages per request.
How does Parse handle scanned documents or low-quality images?
Parse uses a vision model that reads documents the way a human does, not a character-by-character OCR engine. Low-resolution scans, rotated pages, mobile photos, and fax copies are all handled accurately, provided the content is legible.
What languages does Parse support?
Parse supports English, Hindi, Tamil, Telugu, Marathi, Bengali, Gujarati, Kannada, Malayalam, Punjabi, Odia, and Urdu. Mixed-language documents are handled correctly in a single parse request.
Is the markdown output customizable?
The current output format is standard CommonMark markdown. Structure is preserved as faithfully as possible from the original document. Custom output formats are on the roadmap. Contact us to discuss specific requirements.
Built for
The document layer for your AI stack
Ready to start?
See ParseAI on your documents.
Book a 30-minute demo and we'll walk you through a live extraction on your own documents.
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