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Master Zep with our step-by-step tutorial, detailed feature walkthrough, and expert tips.
Sign up for free Zep account at app.getzep.com and create your first project Install the SDK for your preferred language (Python, TypeScript, or Go) and configure API credentials Define your data model with custom entity types and relationships for your business domain Start ingesting conversation data and business information using the simple three
line integration Test context retrieval and optimize configuration parameters for your accuracy and latency requirements
💡 Quick Start: Follow these 2 steps in order to get up and running with Zep quickly.
Explore the key features that make Zep powerful for ai agent memory & context workflows.
Facts carry validity windows. When new information contradicts old, Zep invalidates the old fact rather than deleting it — the agent reasons on the current truth but you can audit history.
Benchmarked at 148ms for 1K graphs and 168ms for 100M graphs — retrieval stays flat as your Context Lake grows.
Access control, retention, legal hold, and audit live in the underlying platform, not glued onto each agent — critical for compliance at enterprise scale.
Expose a Zep memory space as an MCP server; any MCP-compatible client can call it as a first-class memory tool.
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.
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.
Zep's temporal knowledge graph automatically invalidates outdated facts when new information conflicts with existing data.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.
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.
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.
Now that you know how to use Zep, it's time to put this knowledge into practice.
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Tutorial updated March 2026