Graphiti is a backend framework and memory server designed to provide artificial intelligence agents with persistent, time-aware knowledge graph storage. It functions as a memory layer that enables agents to maintain context across long-term interactions by recording and evolving structured data over time.
The system distinguishes itself through a specialized temporal graph database that tracks how entities and relationships change using validity windows. By combining semantic vector similarity, keyword matching, and graph topology traversal, the engine performs hybrid retrieval to locate relevant information. It further refines these results by calculating graph distances from central entities, ensuring that retrieved context is prioritized based on its structural relevance to the query.
The platform supports schema-driven entity modeling, allowing for the enforcement of domain-specific structures on incoming data. It manages the ingestion of raw inputs into structured graphs and performs incremental updates to maintain the knowledge base without requiring full batch recomputation. Through standardized interfaces and protocol support, the system integrates with various large language model providers to automate data extraction and reasoning.
