Zep

Overview

Zep is a developer platform providing long-term memory infrastructure for AI agents and assistants. It stores, indexes, and retrieves conversational memories using a hybrid vector-graph store optimized for LLM applications. Targeted at developers building personalized AI experiences, it stands out with automatic summarization, semantic chunking, and agentic retrieval for context-aware responses.

Key Features

• Hybrid Memory Store - Combines vector embeddings and graph structures for efficient storage and retrieval of conversation history.
• Automatic Summarization - Generates concise summaries of past interactions to maintain context without full history replay.
• Semantic Chunking - Breaks conversations into meaningful units for precise retrieval and reduced token usage.
• Agentic Retrieval - AI-driven search that understands query intent and fetches relevant memories dynamically.
• REST and Python SDK - Simple APIs and client libraries for easy integration into applications.
• Scalable Cloud Backend - Managed service handling high-volume memory operations with automatic scaling.
• Session Management - Tracks user sessions and maintains persistent memory across interactions.

Pricing

Platforms & Requirements

Zep runs as a cloud service accessible via REST API from any platform with HTTP support. Self-hosted version available via Docker for Linux/macOS/Windows. Requires Python 3.8+ for SDK; no native mobile apps.

Integrations & Ecosystem

• LangChain
• LlamaIndex
• OpenAI API
• Anthropic Claude
• PostgreSQL (self-hosted)
• Docker
• Kubernetes
• Webhooks

Alternatives

Reputation

Zep is praised by AI developers for simplifying memory management in production LLM apps, with strong adoption in agent frameworks. Criticisms include occasional latency in high-volume retrieval and limited free tier for scaling tests. Overall positive perception as a specialized tool since 2023 launch.