Zep

Features

Long-term Memory Stores - Provides a persistent storage system for retaining user and session context across multiple AI interactions.

Temporal Knowledge Graphs - Maintains a graph of dated facts to track how user preferences and environments evolve over time.

AI Context Optimization - Fetches concise and relevant information for LLMs to improve response accuracy and reduce hallucinations.

Graph-Based Context Retrieval - Searches for pertinent facts using combined semantic and graph methods to maintain precise context for AI generation.

Knowledge Graphs - Organizes user interaction data as a graph of dated facts to provide persistent memory for AI agents.

Persistent Chat Histories - Saves messages and unstructured data at the user or session level for long-term conversational context.

Stateful LLM Application Servers - Provides a stateful server architecture that manages conversation threads, user preferences, and long-term memory.

Hybrid Vector-Graph Databases - Combines vector embeddings with knowledge graphs to support both semantic and relational queries for high-precision context.

Agent Interaction Memory Stores - Builds a temporal knowledge graph from documents and chats to maintain a persistent memory of users and contexts.

Semantic Retrieval Engines - Uses mathematical embeddings to find relevant context by calculating the distance between queries and stored documents.

Vector Database Orchestrators - Implements a management layer for indexing and retrieving semantic context and unstructured data to reduce LLM hallucinations.

Prompt-Optimized Context Retrieval - Retrieves concise and governed data from a central source to improve AI response accuracy and reduce hallucinations.

Document Versioning - Tracks historical changes to source materials to ensure retrieved context reflects the most current knowledge base state.

User and Session Hierarchies - Organizes chat histories into user and session hierarchies to enable efficient retrieval and privacy-compliant data deletion.

AI Session Privacy Management - Manages the deletion and pruning of conversational AI history to meet regulatory privacy requirements.

Privacy Compliance Tools - Provides utilities for executing data deletion requests and privacy compliance tasks across user and session records.

Zep is a long-term memory layer and persistent storage system for large language model applications. It functions as a memory service and vector database orchestrator that manages chat history, user preferences, and context retrieval to reduce hallucinations in AI agents.

The system maintains a temporal knowledge graph that stores interaction data as dated facts to track how user preferences and environments evolve over time. It combines these knowledge graphs with a store for persisting unstructured message data at the user and session levels.

The platform provides capabilities for AI context optimization through semantic and graph-based search, as well as AI privacy management tools for executing data deletion requests and compliance tasks across user records.

Features