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Agent memory🔴Developer
Z

Zep

Zep provides agent memory capabilities for teams building and operating AI applications. It supports the MCP ecosystem.

Starting atFree
Visit Zep →
💡

In Plain English

Zep provides agent memory capabilities for teams building and operating AI applications. It supports the MCP ecosystem.

OverviewFeaturesPricingGetting StartedUse CasesIntegrationsLimitationsFAQSecurityAlternatives

Overview

Zep is a agent memory product intended for teams building or operating AI-enabled software. The vendor site describes its offering in terms that include: The vendor page could not be reliably extracted during this automated run. This profile is based on the public homepage and pricing route fetched on August 25, 2026; buyers should confirm details that affect purchasing or production architecture directly with the vendor.

For builders, the practical value is reducing the custom work needed to connect, inspect, evaluate, or operate AI applications. Typical workflows include prototyping an assistant, adding the product to an existing application, reviewing behavior with a technical or business team, and creating a repeatable production process. It is best evaluated with a representative workload: connect one real application, define success criteria, measure setup effort and output quality, then review security, data retention, access controls, and export options. Zep advertises or participates in the Model Context Protocol ecosystem in a server role. That can make it easier to expose capabilities to MCP hosts or consume MCP tools without a proprietary integration for every client.

Pricing evidence from the fetched pricing page was not reliably extractable. Free allowances, usage limits, model charges, seats, support, and enterprise controls can materially change total cost. A sensible pilot should therefore test both functional fit and expected monthly volume. Strong use cases include agent memory pilots, internal AI applications, and production systems where teams want a maintained product instead of assembling every operational component themselves.

🦞

Using with OpenClaw

▼

Integrate Zep's context engineering APIs with OpenClaw through REST endpoints or SDKs to provide sophisticated memory and context assembly capabilities for AI agents and workflows.

Use Case Example:

Enhance OpenClaw agents with temporal knowledge graphs and context engineering for personalized, relationship-aware automation workflows.

Learn about OpenClaw →
🎨

Vibe Coding Friendly?

▼
Difficulty:intermediate

Requires API integration and data modeling but provides clear SDKs and documentation for implementation.

Learn about Vibe Coding →

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Editorial Review

Zep delivers sophisticated context engineering capabilities that go far beyond simple conversation memory. Users praise the temporal knowledge graph approach for capturing entity relationships and fact evolution over time. The <200ms retrieval latency and framework-agnostic integration make it suitable for real-time applications. Enterprise features including SOC2 and HIPAA compliance address security requirements. Some users note the credit-based pricing can become expensive at scale, and the graph-based architecture requires more setup than simple memory stores.

Key Features

Temporal Knowledge Graph+

Builds evolving knowledge graphs from conversations and business data, tracking how entities and relationships change over time. Automatically invalidates outdated facts while preserving provenance, ensuring agents access current, accurate information.

Use Case:

Customer support agent understands that a user's payment method was updated last week, invalidating previous 'expired card' status while maintaining history of the resolution process.

Unified Context Assembly+

Automatically ingests and correlates data from chat history, CRM systems, JSON business data, and documents into a single context graph. Retrieves and formats relevant information for LLM consumption in one API call.

Use Case:

Sales agent accessing prospect's conversation history, CRM data, and product interaction logs to provide personalized recommendations based on complete customer journey.

Real-Time Context Retrieval+

Delivers assembled context with <200ms P95 latency using optimized graph traversal and caching. Multiple configuration options balance accuracy, speed, and token efficiency for different use cases.

Use Case:

Voice agent providing immediate, personalized responses during live customer calls without noticeable delays, accessing complete customer context in real-time.

Graph RAG Integration+

Combines relationship-aware retrieval with traditional RAG, understanding connections between entities to surface relevant context. Supports custom entity types and relationship models for domain-specific knowledge.

Use Case:

Healthcare agent understanding patient's medication history, doctor relationships, and treatment outcomes to provide contextually appropriate health guidance.

Custom Context Templates+

Pre-formatted context blocks optimized for different LLM prompting strategies. Allows fine-tuned control over how entities, relationships, and facts are presented to agents.

Use Case:

E-commerce agent receiving customer context formatted with purchase history, browsing patterns, and preference summaries tailored for product recommendation workflows.

Enterprise Security & Compliance+

SOC2 Type 2 certified with HIPAA BAA support, multiple deployment models including BYOK, BYOM, and BYOC. Audit logs, guaranteed SLAs, and data residency controls for regulated industries.

Use Case:

Healthcare organization deploying AI patient assistants with full HIPAA compliance, encrypted data processing, and audit trails for regulatory requirements.

Pricing Plans

Free

$0/month

    Flex

    $125/month

      Flex Plus

      $375/month

        Enterprise

        Custom

          See Full Pricing →Free vs Paid →Is it worth it? →

          Ready to get started with Zep?

          View Pricing Options →

          Getting Started with Zep

          1. 1Sign up for free Zep account at app.getzep.com and create your first project
          2. 2Install the SDK for your preferred language (Python, TypeScript, or Go) and configure API credentials
          3. 3Define your data model with custom entity types and relationships for your business domain
          4. 4Start ingesting conversation data and business information using the simple three-line integration
          5. 5Test context retrieval and optimize configuration parameters for your accuracy and latency requirements
          Ready to start? Try Zep →

          Best Use Cases

          🎯

          Teams adopting agent memory

          ⚡

          AI application pilots

          🔧

          Production workflow standardization

          Integration Ecosystem

          3 integrations

          Zep works with these platforms and services:

          🧠 LLM Providers
          OpenAIAnthropicGoogle
          View full Integration Matrix →

          Limitations & What It Can't Do

          We believe in transparent reviews. Here's what Zep doesn't handle well:

          • ⚠Credit-based pricing can become expensive for high-volume applications with continuous context retrieval needs
          • ⚠Knowledge graph extraction quality depends on conversation richness—sparse technical discussions may not produce meaningful relationship structures
          • ⚠Advanced temporal graph features and enterprise compliance require paid tiers, limiting free tier functionality for production use
          • ⚠Complex graph-based architecture requires more setup and domain modeling compared to simple vector memory stores like Mem0

          Pros & Cons

          ✓ Pros

          • ✓tracks when facts change
          • ✓ingestion-centered pricing suits read-heavy agents
          • ✓several SDK and deployment options

          ✗ Cons

          • ✗credit consumption needs real payload testing
          • ✗free allowance is small
          • ✗webhooks and analytics require a higher tier

          Frequently Asked Questions

          How does Zep's context engineering differ from traditional RAG systems?+

          Traditional RAG retrieves static documents based on similarity. Zep builds temporal knowledge graphs that understand entity relationships and track how facts change over time. This enables queries like 'how has the customer's preference evolved?' that static RAG cannot handle. Zep also assembles context from multiple sources (chat, CRM, business data) in one API call.

          What makes Zep faster than other agent memory systems?+

          Zep achieves <200ms P95 retrieval latency through optimized graph traversal, intelligent caching, and single-shot context assembly. Unlike systems that require multiple tool calls or agentic loops, Zep delivers complete assembled context in one API request, eliminating the round-trip delays that slow down other approaches.

          How does Zep handle fact conflicts and outdated information?+

          Zep's temporal knowledge graph automatically invalidates outdated facts when new information conflicts with existing data. It maintains provenance to source messages and timestamps, allowing agents to reason about when facts were true and how they've changed. This prevents agents from acting on stale information.

          Can Zep integrate with existing agent frameworks like LangChain?+

          Yes. Zep is framework-agnostic with native SDKs for Python, TypeScript, and Go. It integrates with LangChain, LlamaIndex, AutoGen, CrewAI, and custom frameworks through simple API calls. The three-line integration works with any system that can make HTTP requests.

          What deployment options does Zep offer for enterprise customers?+

          Enterprise customers can choose from Managed (fully hosted), BYOK (bring your own encryption keys), BYOM (bring your own model provider), or BYOC (bring your own cloud/VPC). All enterprise plans include SOC2 Type 2 certification, HIPAA BAA support, guaranteed SLAs, and dedicated account management.

          🔒 Security & Compliance

          —
          SOC2
          Unknown
          —
          GDPR
          Unknown
          —
          HIPAA
          Unknown
          —
          SSO
          Unknown
          —
          Self-Hosted
          Unknown
          ✅
          On-Prem
          Yes
          —
          RBAC
          Unknown
          —
          Audit Log
          Unknown
          ✅
          API Key Auth
          Yes
          —
          Open Source
          Unknown
          ✅
          Encryption at Rest
          Yes
          ✅
          Encryption in Transit
          Yes
          Data Retention: configurable
          Data Residency: CONFIGURABLE
          📋 Privacy Policy →🛡️ Security Page →
          🦞

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          What's New in 2026

          •Launched Graphiti open-source temporal context graph library for transparent, extensible memory systems
          •Introduced unified context engineering platform combining Graph RAG, agent memory, and automated context assembly
          •Added enterprise deployment flexibility with BYOK, BYOM, and BYOC options alongside managed cloud service
          •Achieved SOC2 Type 2 certification and HIPAA BAA support for regulated industry applications

          Alternatives to Zep

          Letta

          AI Agent Framework

          Framework and cloud service for building stateful AI agents that remember, learn continuously, and improve over time — the successor to MemGPT.

          LangMem

          AI Memory & Search

          LangChain memory primitives for long-horizon agent workflows.

          Supermemory

          AI Memory & Search

          Supermemory is the memory and context layer for AI agents — a graph-based memory API with extractors, connectors, and retrieval for personal apps and enterprise stacks.

          Cognee

          AI Memory & Search

          Cognee is an open-source agent memory platform that builds a hybrid knowledge graph and vector index from your data so LLM agents recall structured facts, not just nearest-neighbour text chunks. Free Hobby, usage-based Growth, custom Enterprise.

          View All Alternatives & Detailed Comparison →

          User Reviews

          No reviews yet. Be the first to share your experience!

          Quick Info

          Category

          Agent memory

          Website

          www.getzep.com
          🔄Compare with alternatives →

          Try Zep Today

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          More about Zep

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