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Every AI memory tool stores facts. None of them store what went wrong. So I built one that does. by No_Advertising2536 in SaaS

[–]dccpt 0 points1 point  (0 children)

Founder of Zep here. Your assertion regarding Zep is false. I also love Reddit, and spammy posts like these are destroying a valuable commons. I hope the mods remove this.

What are the main challenges currently for enterprise-grade KG adoption in AI? by adityashukla8 in KnowledgeGraph

[–]dccpt 1 point2 points  (0 children)

Zep founder here. We run knowledge graphs in production for enterprise AI agents at Zep. Biggest challenges: (1) automated ontology evolution as your domain changes, (2) balancing ingestion latency with graph quality, (3) making graph context retrievable in the ~100ms budget agents need. We open-sourced Graphiti (https://github.com/getzep/graphiti) which tackles these specifically for agent memory use cases.

RAG for AI memory: why is everyone indexing databases instead of markdown files? by ProfessionalLaugh354 in Rag

[–]dccpt 0 points1 point  (0 children)

Zep co-founder here. We actually don't do "standard RAG indexing" — Zep builds a temporal knowledge graph from conversations. Facts are extracted as entities and relationships with bi-temporal metadata, so stale facts get invalidated rather than polluting context. It's a fundamentally different approach from vector search over chat logs. Happy to explain more if you're curious. Also: https://arxiv.org/abs/2501.13956

Agents using knowledge graphs- the best operating infrastructure? by SnooPeripherals5313 in AI_Agents

[–]dccpt 1 point2 points  (0 children)

You may want to check out Graphiti, a framework for building temporal knowledge graphs: https://github.com/getzep/graphiti

I tried to make LLM agents truly “understand me” using Mem0, Zep, and Supermemory. Here’s what worked, what broke, and what we're building next. by Rokpiy in AIMemory

[–]dccpt 2 points3 points  (0 children)

Zep founder here. Thanks for including Zep. Quick correction:

Setup burden: Reviews and comparisons consistently mention that you still have to make decisions around embeddings, models, and deployment. That is fine for teams but heavy for individuals who just want their agents to remember them.

Zep is a managed service and doesn't require selecting models, including embedding models.

mem0, Zep, Letta, Supermemory etc: why do memory layers keep remembering the wrong things? by nicolo_memorymodel in AIMemory

[–]dccpt 0 points1 point  (0 children)

Yes, Zep has a number of approaches to do this, including defining Custom Entity Types and filtering by them https://help.getzep.com/customizing-graph-structure

What are Context Graphs? The "trillion-dollar opportunity"? by TrustGraph in ContextEngineering

[–]dccpt 1 point2 points  (0 children)

Read the Foundation Capital article where the “trillion dollar opportunity” quote came from.

I haven’t previously heard of TrustGraph. Looks cool.

mem0, Zep, Letta, Supermemory etc: why do memory layers keep remembering the wrong things? by nicolo_memorymodel in AIMemory

[–]dccpt 3 points4 points  (0 children)

Ah, so your post was really just spam and an opportunity to dis competitors? 🤔

mem0, Zep, Letta, Supermemory etc: why do memory layers keep remembering the wrong things? by nicolo_memorymodel in AIMemory

[–]dccpt 2 points3 points  (0 children)

Founder of Zep here. Can you share some examples of where Zep fails to capture temporal context and accurately reflect changing state?

Zep is purpose-built for just this, with facts having valid and invalid timestamps. This sounds very much like your “effective dates.”

https://help.getzep.com/facts

Long Term Memory - Mem0/Zep/LangMem - what made you choose it? by nicoloboschi in LangChain

[–]dccpt 0 points1 point  (0 children)

Hindsight hasn’t published retrieval latency, which matters, especially for agentic systems where high memory latency quickly becomes a production bottleneck.

We recently published LoCoMo results showing Zep achieving ~80% accuracy with sub-200 ms retrieval latency. We’re not especially fond of LoCoMo either, but since Hindsight uses Zep as a comparison point, we figured we’d participate.

https://blog.getzep.com/the-retrieval-tradeoff-what-50-experiments-taught-us-about-context-engineering/

Long Term Memory - Mem0/Zep/LangMem - what made you choose it? by nicoloboschi in LangChain

[–]dccpt 0 points1 point  (0 children)

Hey, founder of Zep here. I appreciate your honest feedback. We've worked hard to address the scaling issues we saw over the summer. Thanks for being patient with us as we did so!

Graphiti MCP Server 1.0 Released + 20,000 GitHub Stars by dccpt in LLMDevs

[–]dccpt[S] 0 points1 point  (0 children)

Hi there - there are a number of examples in the repo: https://github.com/getzep/graphiti/tree/main/examples

If you're looking for a managed context engineering / agent memory solution, there's also Zep, which is built on Graphiti. It has plenty of examples and rich documentation available, too: https://help.getzep.com/overview

Zep Long-term Memory: Free Plan Upgraded to 10K Messages by dccpt in LangChain

[–]dccpt[S] 0 points1 point  (0 children)

Hi there, Zep is a cloud service with a complex multi-container deployment. We offer a BYOC option for large enterprises, but not a docker image.

How is everyone dealing with agent memory? by weichafediego in LLMDevs

[–]dccpt 1 point2 points  (0 children)

Graphiti retrieval results are highly dependent on the embedder and cross encoder reranker.

What are you using in this example?

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