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Zep

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Enterprise-grade memory infrastructure for AI agents based on temporal context graphs

Adicionado em:13 de jul. de 2026
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AI agent memorytemporal context graphsContext Lakeenterprise AIagent infrastructurepersistent memory

Informações da ferramenta

O que é Zep?

Zep delivers persistent, temporal memory for AI agents via context graphs and a Context Lake that ingests sources, tracks facts over time, preserves provenance, governs access, and serves token-efficient context at enterprise scale.

Recursos principais

  • Temporal Context Graphs

    Builds graphs from any source (chat history, business data, user interactions) to track entities, facts, and how they change over time, with automatic invalidation of contradicted facts while retaining history.

  • Context Lake

    Manages millions of context graphs as a governed, unified system powered by Zep’s proprietary Context Graph Engine, applying a data-lake pattern to agent context.

  • Sub-200ms Retrieval

    Maintains retrieval latency under 200 milliseconds (p95) regardless of graph size or count, scaling from 10K to 100M graphs.

  • Governed at the Substrate

    Provides attribute-based access control, retention policies, and audit/API logs that apply across every graph, query, and layer.

  • Provenance Preserving

    Traces every fact in the graph back to the source episode that produced it, enabling full audit of answers.

  • Observations

    Analyzes graph structure to surface patterns, recurrences, and co-occurrences as Observations that give agents a global perspective beyond individual facts.

  • Built-in Observability and Analytics

    Includes analytics for graphs created, users created, episodes added, and retrieval activity.

  • Flexible Deployment Models

    Supports Cloud, Cloud + Your Own Keys, and Bring Your Own Cloud deployment options.

Casos de uso

  • #1

    Persistent AI Agent Memory

    Provides managed memory of users, business data, and work done so agents can deliver reliable, personalized behavior at scale.

  • #2

    Long-Running Agent Context

    Supports long-running agent memory with temporal awareness, including benchmarks on LoCoMo and LongMemEval.

  • #3

    Enterprise Agent Stack Memory Layer

    Serves as governed, scalable memory infrastructure for enterprise AI agent deployments with compliance and audit needs.

Melhor para:AI teamsEnterprises building AI agentsDevelopers of production AI agents

Planos de preços

Enterprise pricing is offered. Deployment models include Cloud, Cloud + Your Own Keys, and Bring Your Own Cloud. Book a demo and sign-up options are available.

Alternativas

Perguntas frequentes

What is Zep?
Zep is enterprise-grade memory infrastructure for AI agents based on temporal context graphs with sub-200ms retrieval and governance. It delivers persistent, temporal memory via context graphs and a Context Lake.
How does Zep provide memory for AI agents?
Zep builds temporal context graphs from sources like chat history, business data, and user interactions to track entities and facts over time. It preserves provenance, governs access, and serves token-efficient context at scale.
What deployment options does Zep support?
Zep supports Cloud, Cloud + Your Own Keys, and Bring Your Own Cloud deployment models.
How fast is retrieval with Zep?
Zep maintains retrieval latency under 200 milliseconds (p95) regardless of graph size or count, scaling from 10K to 100M graphs.
Is Zep suitable for enterprise AI agent deployments?
Yes. Zep serves as governed, scalable memory infrastructure with attribute-based access control, retention policies, audit/API logs, provenance tracking, and SOC 2 compliance for enterprise use.

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Informações da ferramenta

Modelo de preçosPaid
CategoriaChatbots e LLM
Tags
AI agent memorytemporal context graphsContext Lakeenterprise AIagent infrastructurepersistent memory
IdiomaInglês
Última atualização16 de jul. de 2026