Best AI Memory Frameworks for LLMs on Reddit
187 reddit mentions across r/LLMDevs, r/LocalLLaMA, r/KnowledgeGraph, r/AIMemory, r/Rag and 30+ more subreddits
"Cognee ROCKS! Im currently building an app and the graph layer is planned to be on top of Cognee. The fact that i can build my own KGs logics, how to create, how to retrieve, the vectors... is amazing. I will be using multiple pipelines and so far Cognee is capable of it. I really think you guys can be the LiteLLM for KGs/GRAGs."
"For deep technical docs like manuals and datasheets, the graph schema flexibility matters more than which tool you pick. Cognee gives you more control over entity types and relationship layers, which helps when your terminology is domain-specific. Mem0 is faster to wire up but the graph tends to stay fragmented — entities from separate docs don't link unless you do extra work."
"Cognee is super interesting. I've been trying out different ways of integrating it. My first experiment is to keep an obsidian wiki with pages that describe high level concepts in my system — used Claude Opus and GPT-5.5 to write the wiki. The boundary that helps a ton is templating wiki pages depending on type, and preventing granular 'current state of this' entries which are endless."
"Cognee was built with exactly this kind of structured memory purposes in mind — manuals, datasheets, specs. The graph construction is designed to preserve hierarchical relationships and cross-references that matter a lot in that domain. We also handle incremental updates pretty well which helps when you're dealing with versioned documentation."
"Cognee is a building block where you can build your pipeline the way you want it from where you want it. Yes it has its own extraction auto 'default' pipeline but you should build your own. Cognee is made of building blocks — use them and build by yourself a pipeline that fits your threshold criteria."
"I was just starting the process of defining and building a benchmarking suite within my VS Code extension, which provides stored context ('memory') in a graph-vector-SQL backend (using Cognee as the core storage system). No affiliation."
"I'm exploring a memory system called Cognee that has a few different facets for memory and semantic search."
"Have you looked into Mem0? I was personally unable to use it since my entire stack is built with LangChain and Mem0 does not have LangChain integration yet. If your set up is different, you should be able to incorporate memory using Mem0."
"For technical documents like manuals and datasheets feeding customer support agents: Graphiti (Zep's graph layer) is probably your strongest option. Built for temporal knowledge graphs with entity relationships, handles fact updates and supersession better than the others. Most production-ready for the use case you're describing."
"I've tried Letta, Zep, Mem0 on and off again but lots of tedious problems impede my progress. I need strong long-term context, preventing drift across sessions and carrying forward the right historical context without bloating the prompt. Or perhaps neither are what I would've been suggested."
"Memgpt was the paper. Then they renamed it Letta. But they might have done much more to that library since the last time I checked was a while ago. The first two authors of the MemGPT paper and their supervisors are co-founders of the Letta company."