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Rahul Agarwal
Founder | Agentic AI... • 2m
Turn your laptop into a powerful RAG engine. The world’s smallest vector database. I've explained below. If you’re building RAG today, you’re facing a brutal reality: 𝗖𝗹𝗼𝘂𝗱 𝘃𝗲𝗰𝘁𝗼𝗿 𝗗𝗕𝘀 𝗮𝗿𝗲 𝗲𝘅𝗽𝗲𝗻𝘀𝗶𝘃𝗲 and 𝗼𝗻-𝗽𝗿𝗲𝗺𝗶𝘀𝗲 𝘀𝗲𝘁𝘂𝗽𝘀 𝗮𝗿𝗲 𝗮𝗿𝗲 𝘁𝗼𝘂𝗴𝗵 𝘁𝗼 𝗺𝗮𝗻𝗮𝗴𝗲. LEANN completely rewrites this story. A 1GB dataset turning into a 7GB vector index? That’s the norm with Pinecone, Weaviate, Chroma etc. LEANN stores only 3% of what traditional vector databases need, while keeping retrieval accuracy nearly identical. 𝗛𝗼𝘄 𝗜𝘁 𝗪𝗼𝗿𝗸𝘀 (𝗦𝗶𝗺𝗽𝗹𝗲 𝗩𝗲𝗿𝘀𝗶𝗼𝗻) • 𝗦𝗲𝗹𝗲𝗰𝘁𝗶𝘃𝗲 𝗿𝗲𝗰𝗼𝗺𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻 → compute embeddings only when needed • 𝗚𝗿𝗮𝗽𝗵-𝗯𝗮𝘀𝗲𝗱 𝗽𝗿𝘂𝗻𝗶𝗻𝗴 → keep only the high-value structure • 𝗖𝗦𝗥 𝘀𝘁𝗼𝗿𝗮𝗴𝗲 → ultra-compact memory layout • 𝗢𝗻-𝗱𝗲𝘃𝗶𝗰𝗲 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 → perfect for edge + personal AI ✅ 𝗪𝗵𝘆 𝗟𝗘𝗔𝗡𝗡 𝗜𝘀 𝗮 𝗕𝗿𝗲𝗮𝗸𝘁𝗵𝗿𝗼𝘂𝗴𝗵 𝗳𝗼𝗿 𝗠𝗼𝗱𝗲𝗿𝗻 𝗥𝗔𝗚 • 50× smaller indexes • 90%+ search accuracy • <2 seconds search latency • Runs fully local, zero cloud dependency • Handles millions of docs on a laptop ✅ 𝗣𝗲𝗿𝗳𝗲𝗰𝘁 𝗳𝗼𝗿 𝗟𝗼𝗰𝗮𝗹, 𝗣𝗿𝗶𝘃𝗮𝘁𝗲, 𝗥𝗲𝗮𝗹-𝗪𝗼𝗿𝗹𝗱 𝗥𝗔𝗚 • Run your entire RAG pipeline on your laptop • Build privacy-focused assistants without sending data to the cloud • Store long-term agent memory efficiently If you work with vector search, agents, or long-context AI… this is one project you 𝗰𝗮𝗻𝗻𝗼𝘁 𝗮𝗳𝗳𝗼𝗿𝗱 𝘁𝗼 𝗶𝗴𝗻𝗼𝗿𝗲. LEANN is built for the new era of privacy-focused, decentralized, and efficient RAG systems. GitHub: https://lnkd.in/gtsjcV8T ✅ Repost this for others who can benefit from this.
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