PDF Reader parses document structure with AI, extracts the key information, and turns it into a visual mind map — making deep paper reads and technical document skims faster than ever.
Open the appDrag and drop or click to upload a paper, report, or technical document
Detects document structure; extracts sections, abstracts, and key claims
Turns the document's logical flow into a clear visual mind map
One-stop experience from upload to knowledge visualization
AI-driven document understanding recognizes the section structure, figures, formulas, and citations inside a PDF, and builds an accurate content outline.
Turns the document's logical flow and key ideas into a hierarchical mind map. The knowledge structure becomes visible at a glance.
Automatically annotates core claims, key data points, and conclusions so you can jump to what matters and skip the rest.
Optimized for academic papers: extracts the research question, methods, experimental results, and conclusions to help you grasp each contribution.
Parses both Chinese and English PDFs; detects the language automatically and applies the appropriate structural processing. Ideal for international reading.
No install. Use it in any browser. Processing runs in the cloud, so large files are no problem.
Every PDF read, more efficient
Upload a paper; the model deconstructs the research framework and produces a mind map covering methodology, experiments, and conclusions. Especially useful during literature review.
Facing a 50-page technical spec or API reference? Get a structured overview. Helps engineers master the core architecture and interfaces before writing any code.
Upload industry reports, whitepapers, or financial reports; the model extracts key numbers and conclusions. Decision-makers get a full picture in minutes.
Teachers upload textbook chapters and get a knowledge-framework diagram. Students turn lecture slides into mind maps to organize their learning.
Upload a PDF and get a complete structured mind map in seconds. Free to use, no sign-up.
Visit PDF ReaderCrawls trending HuggingFace papers; an LLM produces summaries and categories, refreshed daily with the latest AI progress.
17 AI agents collaborating across HR, finance, and IT operations — natural-language-driven office workflows.
Transparent LLM API proxy with automatic context compression. One-line integration cuts spend by 30–60%.
A tiered knowledge database built for AI agents — L0/L1/L2 summaries, MCP integration, and session memory.
Import Bilibili videos or upload local files. AI transcription + contextual Q&A + auto notes makes video learning more efficient.