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Honest Comparison

Zep and Hebbrix both care about AI memory.
They just think about it differently.

Zep focuses on temporal knowledge graphs and enterprise context engineering. Hebbrix focuses on versioned memory, adaptive retrieval, and explicit Outcome Memory. Both are valid approaches. This breakdown will help you pick.

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Two philosophies, one problem

Zep's philosophy

Graph-first context engineering

Zep builds temporal knowledge graphs from conversations and uses them to enrich agent context. Strong focus on enterprise features, open-source Community Edition, and integration with LangGraph/LangChain ecosystems. Context engineering as a first-class concept.

Temporal graphsOpen source CEEnterprise focusLangGraph native
Hebbrix's philosophy

Versioned memory with measured outcomes

Hebbrix combines current and historical memory, temporal graph provenance, adaptive retrieval, and an Outcome Memory loop that learns only when an integration reports real delayed results.

Versioned memoryAdaptive searchOutcome learningTemporal graphMemory lifecycle

Where the approaches diverge

Both platforms handle the basics well. These are the meaningful differences.

Memory architecture
Zep

Flat memory with temporal knowledge graphs layered on top. Good for timeline-based reasoning.

Hebbrix

Versioned current and historical memory with provenance, supersession, operational lifecycle tiers, and explicit deletion controls.

Search approach
Zep

Graph-based retrieval using temporal knowledge graphs. Strong at finding entity connections over time.

Hebbrix

Adaptive hybrid retrieval across dense, sparse, graph, temporal, facet, and calibrated ranking signals with confidence metadata.

Learning
Zep

Temporal knowledge graph (Graphiti) that extracts and invalidates facts as they change over time.

Hebbrix

Outcome Memory records decision receipts and propensity before action, then learns from delayed reported outcomes with posterior uncertainty and correction semantics.

Memory lifecycle
Zep

Temporal knowledge graph that tracks fact validity over time; you tune retention to your needs.

Hebbrix

Temporal validity and supersession retain history while usage, recency, importance, and corrections inform retrieval. Deletion remains explicit.

Choosing the right fit

Zep might be right if
You need temporal reasoning about when things happened
You want an open-source Community Edition to self-host
Your primary framework is LangGraph and you want native integration
Timeline-based knowledge graphs are central to your use case
Hebbrix is built for you if
You want memory to learn from explicitly reported action outcomes
You need adaptive search with multiple relevance and confidence signals
You need current truth plus retained temporal history and provenance
Your agents should feel like they genuinely know their users over time
You want OpenAI-compatible drop-in with memory built in

Try it and decide

The free tier gives you enough room to build something real and feel the difference.

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