Graphiti
Build personalized AI agents that learn from dynamic data
418 followers
Build personalized AI agents that learn from dynamic data
418 followers
Graphiti is Knowledge Graph-based memory for AI agents. Automatically build rich graphs from changing business data & chat histories. Enable your Python agent with fast access to relevant, accurate data, even as it evolves over time. Visit our GitHub repo!
Graphiti
🚀 Hey Product Hunt!
I'm Daniel, the founder of Zep.
I want to introduce you to Graphiti, an open-source Temporal Knowledge Graph framework that gives AI agents the ability to learn and retain information over time, just like humans do. 🤖
Graphiti was inspired by Microsoft GraphRAG, but has a key architectural difference: It understands how newly ingested data might change existing data, and is purpose built for data that evolves over time.
Why does this matter? Imagine you tell a food delivery app that you've adopted veganism, but it keeps recommending your once-favorite burger joint. Or picture a sales assistant that forgets a key client's purchasing history and constraints, resulting in tone-deaf product pitches. That's the kind of experience that frustrates users and undermines trust in AI.
With Graphiti, AI agents can reason with evolving data, enabling more personalized, context-aware interactions. Whether you're building a chatbot, LLM-powered assistant, or a next-gen AI system, Graphiti provides the foundation for fast, accurate long-term memory.
We've implemented Graphiti in Zep, our memory layer for enterprise AI agents, and wrote a paper on how Zep and Graphiti perform versus other approaches to agent memory (it's the State of the Art!). You can find an overview here or read the paper on arXiv.
⏱️ Quick start → Docs
👀 Repo → GitHub
📄 Paper → arXiv
📖 Learn more → Docs
💡We'd love to hear your thoughts—how might Graphiti offer value to the products you're building? Let us know in the comments!
@daniel_chalef @sonu_goswami2 thank you!
Congratulations to you and the entire team, @daniel_chalef. Improvements in ASR, LLM, and TTS inference are fantastic, but adding intelligent long-term memory completes the puzzle. We’ve been waiting for this!!
Graphiti
@adrianmullan thank you!
Stripo.email
Excited to see this in action! AI remembering past interactions is key for personalization—Graphiti sounds like the missing piece. What’s next on your roadmap?
Graphiti
@marianna_tymchuk We just added custom ontologies and currently working on a few more features to to fully utilize them. We are also looking for community suggestions! You can find us at https://discord.gg/2JbGZQZT
Graphiti
@marianna_tymchuk Thanks! Right now we are working on a project that enables users to add a custom entity schema to increase the breadth and quality of data extraction, as well as enhance search capabilities.
Graphiti gives chatbots memory that updates over time. 🧠⌛
Graphiti's approach is superior to classic RAG because it stores information in a queryable Knowledge Graph which replaces big text dumps that usually overstuff context windows.
Not only does this mean you no longer have to keep reminding chatbots of things you've already told them, but they can start to reason over data and information that changes over time, like your affinity for certain brands or the number of pets or relatives you might need to take on a trip.
Graphiti is open source and published under the Apache license.