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Free tool that auto-generates conversational, browsable documentation for any public GitHub repo, from the makers of Devin.
AI creation studio that gathers scattered notes and ideas, then helps shape them into articles, slides, videos, or webpages.
An AI-powered learning platform that turns sources into concept maps, flashcards, quizzes and summaries with multi-model chat.
Developer framework and LlamaParse service for parsing documents and building AI agents and RAG workflows over them.
Real-time web search and content-extraction API that grounds AI agents with fresh, structured data for research and RAG.
No public pricing
No public pricing
No public pricing
- ✦AI-generated documentation for GitHub repos
- ✦Conversational Q&A about a codebase
- ✦Browsable index of popular repositories
- ✦Deep code indexing via Devin
- ✦Central capture space for saved articles, videos, and notes
- ✦AI prompts that surface connections and gaps in collected ideas
- ✦Generates articles, slide decks, videos, and webpages from source material
- ✦Prebuilt style templates for slides and pages
- ✦Available as desktop app, browser extension, and mobile app
- ✦Skill and prompt library for specific creation tasks
- ✦Concept map builder
- ✦Flashcards with spaced repetition
- ✦AI quiz and summary generation
- ✦Import from PDFs, YouTube, websites, PubMed and arXiv
- ✦Multi-model AI chat (GPT, Claude, Gemini, Qwen)
- ✦Cross-format conversion and sharing
- ✦LlamaParse document parsing and extraction
- ✦Open-source framework for AI agents and workflows
- ✦Document indexing for retrieval/RAG
- ✦Prebuilt solutions by industry and use case
- ✦Free starter credits for LlamaParse
- ✦Real-time web search API
- ✦Page content extraction and crawling
- ✦LLM-optimized structured/chunked output
- ✦Built-in PII and prompt-injection filtering
- ✦High-throughput, low-latency infrastructure
- ✦Drop-in integrations with major LLM providers
- →Understanding an unfamiliar codebase quickly
- →Onboarding to open-source projects
- →Answering questions about repo internals
- →Creators consolidating research into finished blog posts or scripts
- →Professionals turning meeting notes into structured reports
- →Teachers converting lesson ideas into slides and video lessons
- →Product managers organizing scattered feedback into insights
- →Visualizing and studying complex topics
- →Turning research sources into study materials
- →Literature review and dissertation prep
- →Parse complex documents for AI apps
- →Build RAG and agent workflows
- →Automate invoice and claims processing
- →Search across technical documents
- →Grounding AI agents with live web data to reduce hallucination
- →Building research or retrieval-augmented generation (RAG) applications
- →Powering AI-driven search assistants
- →Enterprise-scale agents needing reliable web access