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✨ Document PARSING API

Make AI Agents Understand Documents Like Humans Do

Powered by layout analysis, the ComPDF AI parsing engine can identify and label 30+ document elements. It goes beyond extraction - understanding structure, restoring logic, and delivering high-quality structured data to support RAG knowledge bases and document automation workflows.

Document Ready

Annual_Report_2024.pdf · 2.4 MB

Layout Analysis
OCR Processing
Metadata Extraction
Document Upload

What You See Is What You Get — Try the Online Demo Now

Upload different document types and see ComPDF AI in action.

Industrial ManualFinancial ReportsPaperExam PaperHandwritten NotesNewspaper
1 / 1
Industrial Manual
MarkdownJSON
Start Now

From Raw Documents to AI-Ready Knowledge

See how ComPDF AI transforms unstructured documents into structured, machine-ready knowledge.

Step 1:

Document Preprocessing

Enhance image quality for more accurate parsing

Step 2:

AI Layout Analysis

Understand page layout and structure like a human reader

Step 3:

Reconstruct Logical Structure

Restore reading order and hierarchy, then output LLM-friendly structured data

Before
After
Enhancing...

Open-Source SDK for Fast AI Document Parsing

Powered by the open-source Python SDK docslight-lite, developers can quickly integrate high-performance document parsing with support for both local deployment and cloud-based API calls.

Copy and run the command below in your terminal to get started in seconds.

from docslight import DocSlightclient = DocSlight(mode="cloud", api_key="your api key", base_url = "https://api-server.compdf.com")file_path = "/Users/yourname/Documents/invoice.pdf"result = client.parse(file_path)print(result.to_markdown())

What Can You Build with Parsed Results?

Document Parsing API

RAG Knowledge Bases

Convert documents into structured data to power vector databases and AI assistants to improve retrieval efficiency up to 99%.

Learn MoreRAG Knowledge Bases
Document Parsing API

LLM Applications

Provide clean, structured training data for fine-tuning and model improvement, enabling more accurate and reliable outputs.

Learn MoreLLM Applications
Document Parsing API

Data Processing Pipelines

Use parsed output in ETL workflows and sync data automatically to CMS, databases, or automation platforms.

Learn MoreData Processing Pipelines
Document Parsing API

AI Agent Workflows

Give AI agents a stronger understanding of documents so they can reason, retrieve, and act with greater accuracy.

Learn MoreAI Agent Workflows

Beyond OCR, Built for LLMs

Advanced document parsing designed for RAG systems and fully automated business workflows.

Reading Order Reconstruction

Automatically detects reading flow across columns, side notes, and complex layouts

Page 1
Reading order is
crucial for
understanding
the structure
multi-column
documents and
complex layouts
in modern PDFs
especially in
academic papers
and technical
reports
1

Table Recognition

Supports merged cells, borderless tables, and cross-page table reconstruction

Financial Report Q1-Q3Page 3
Table 2.1 - Quarterly Performance
Quarter
Revenue
Growth
Target
Q1 2024
$120K
↑15%
$115K
Q2 2024
$145K
↑21%
$140K
Q3 2024
$168K
↑16%
$160K

Formula Recognition

Accurately capture inline and block formulas, converting OCR output to LaTeX and Markdown.

Physics FundamentalsPage 42

Mass-energy equivalence in theoretical physics...

E=mc²
LaTeX: E = mc^2

Related equations:

∫ f(x)dx = F(x) + C
x = (-b ± √(b²-4ac)) / 2a

Heading Understanding

Detect H1–H6 structures to build document outlines for better RAG indexing.

Table of ContentsPage ii
Document Outline
Annual Report 2024H11
Executive SummaryH22
Key AchievementsH33
Financial HighlightsH34
Market AnalysisH25
Industry TrendsH36

Handwriting Recognition

Optimize OCR to capture approvals, signatures, and handwritten notes.

Contract AgreementPage 1

This agreement is binding between all parties.

Effective date: May 8, 2026

Status:

✓ Approved

Authorized Signature:

John Chen

Margin Notes:

"Please review"
"Call later"
Handwriting detected • 1 approval • 1 signature • 2 notes

Header, Footer, Stamp, and Watermark Detection

Extract critical elements while filtering out noisy page artifacts

Company ConfidentialInternal Document
© 2024 Corporation Inc.Page 1 of 15

Lorem ipsum dolor sit amet, consectetur adipiscing elit.

Sed do eiusmod tempor incididunt ut labore et dolore magna.

Ut enim ad minim veniam, quis nostrud exercitation ullamco.

CONFIDENTIAL
APPROVED05/08/26
HeaderFooterWatermarkStamp

ComPDF AI vs. Traditional Document Parsing

A smarter, more accurate, and easier-to-integrate parsing solution

Proprietary Layout Analysis Model

More than content recognition. ComPDF AI understands document structure and distinguishes complex elements with up to 99% parsing accuracy.

Advanced Table Recovery

30+ Labels Recognition

Native Markdown / JSON / TXT Output

99% Parsing Accuracy

✨ BENCHMARKS

Faster, Ultra-lightweight, More Accurate, Proven in Benchmarks

Backed by independent third-party evaluations and industry benchmarks, the ultra-lightweight ComPDF AI model(0.9B) achieves SOTA-level performance and capabilities.

Benchmark Parsing Performance Leaderboard

Total ScoreOVERALL
Complex document parsing accuracy
96.45ComPDF AI
95.75MinerU2.5-Pro
95.22GLM-OCR
94.93PaddleOCR-VL-1.5
94.18PaddleOCR-VL
93.74Youtu-Parsing
93.70Ovis2.6-30B-A3B
93.33Logics-Parsing-v2
93.26FireRed-OCR
93.04MinerU-2.5
Text
0.032ComPDF AI
0.035Ovis2.6-30B-A3B
0.036MinerU2.5-Pro
0.037FireRed-OCR
0.038PaddleOCR-VL-1.5
0.040PaddleOCR-VL
0.041Logics-Parsing-v2
0.044GLM-OCR
0.044Youtu-Parsing
0.045MinerU-2.5
Formula
97.76ComPDF AI
97.45MinerU2.5-Pro
97.18GLM-OCR
96.89PaddleOCR-VL-1.5
95.91PaddleOCR-VL
95.77MinerU-2.5
95.65Logics-Parsing-v2
93.63Youtu-Parsing
95.44FireRed-OCR
95.17Ovis2.6-30B-A3B
Table
94.80ComPDF AI
93.42MinerU2.5-Pro
92.83GLM-OCR
92.02Youtu-Parsing
91.67PaddleOCR-VL-1.5
90.65PaddleOCR-VL
89.44Ovis2.6-30B-A3B
88.42Logics-Parsing-v2
88.04FireRed-OCR
87.88MinerU-2.5
Reading Order
0.116Youtu-Parsing
0.120MinerU2.5-Pro
0.130PaddleOCR-VL-1.5
0.130MinerU-2.5
0.131ComPDF AI
0.131FireRed-OCR
0.133GLM-OCR
0.135PaddleOCR-VL
0.135Ovis2.6-30B-A3B
0.137Logics-Parsing-v2
Data source: OmniDocBench Leaderboard

Flexible Integration and Deployment Options

Support for cloud APIs, self-hosted deployment, and custom model development to meet the needs of different business stages and scenarios.

Cloud API

The fastest way to integrate. Usage-based pricing and broad language support for Python, Java, Node.js, and Go help you connect intelligent document processing capabilities in no time.

View API Docs

Best for rapid validation and small to mid-sized applications

Self-hosted Deployment

Delivered through Docker-based containerization, with data kept fully within your environment and GPU acceleration supported for high-security, high-performance industries such as finance and government.

Request a Solution

Best for large-scale processing and high-security requirements

Custom-Tuned Service

Fine-tuned for your specific document types, with end-to-end services covering data labeling, model training, and deployment to maximize parsing performance and scenario fit.

Talk to an Expert

Best for non-standard documents and maximum accuracy requirements

Build Smarter Document Workflows Today

Join 10,000+ developers worldwide and power your next intelligent document processing workflow with ComPDF AI.

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