Introducing PDF to Markdown Support in Adobe PDF Extract API

Developers have been using the Adobe PDF Extract API to programmatically unlock structured content from PDFs with high-fidelity JSON output. Today, we’re expanding that capability with a highly requested addition:

🚀 PDF to Markdown Output Is Now Available

In addition to structured JSON, the Extract API can now convert PDFs directly into clean, well-formatted Markdown.

This gives you two powerful output options:

• Structured JSON → Ideal for data pipelines, analytics, compliance workflows, and fine-grained structural processing.

• Markdown → Optimized for LLM ingestion, documentation systems, search indexing, and content publishing workflows.

Same extraction intelligence. New output format.

Why Markdown?

If you're building modern AI or content workflows, chances are you’re transforming JSON into Markdown somewhere downstream anyway.

Now you don’t have to.

The new Markdown output:

• Preserves document hierarchy (headings, sections)

• Converts tables into native Markdown table syntax

• Maintains logical reading order

• Preserves lists and inline formatting

• Embeds figures as base64 for flexible downstream handling

The result: LLM-ready content out of the box.

No additional parsing. No custom transformers. No brittle formatting logic.

Built for AI & Developer Workflows

This new option is especially valuable for:

🔎 Retrieval-Augmented Generation (RAG)

Generate clean Markdown chunks for vector indexing without building a post-processing layer.

🤖 LLM Prompt Pipelines

Feed structured, readable content directly into prompts or fine-tuning datasets.

📚 Documentation Migration

Convert large PDF documentation libraries into Markdown for static site generators (e.g., Hugo, Docusaurus, MkDocs).

🔄 Content Modernization

Move legacy PDF content into searchable knowledge bases with minimal transformation logic.

When Should You Use JSON vs. Markdown?

You now choose the format that best fits your architecture.

🔭 What’s Next: Chunking for AI-Ready Workflows

We’re not stopping here.

We know that developers building LLM-powered applications often need more than clean content — they need intelligently segmented content.

Stay tuned for further development as we plan to introduce chunking capabilities directly within the Extract API. This will help developers automatically break down PDF content into structured, semantically meaningful chunks — optimized for:

• Vector database ingestion

• Retrieval-Augmented Generation (RAG)

• Context window management

• Fine-tuning dataset preparation

Our goal is to reduce the amount of custom preprocessing logic developers need to build when integrating PDFs into AI systems.

Learn More

You can explore the full PDF Extract API documentation here:
👉 https://developer.adobe.com/document-services/docs/overview/pdf-extract-api/