MemoriGraph

About MemoriGraph

Give Your AI a Brain, Not Just a Buffer

One of the biggest hurdles in modern Artificial Intelligence development is the "amnesia" problem. While Large Language Models (LLMs) are brilliant at processing immediate inputs, they often struggle to retain long-term context or understand the intricate relationships between data points over time. Enter MemoriGraph, an open-source API designed to bridge this gap by enabling developers to build AI with sophisticated, contextual memory.

Beyond Vector Databases

Most current memory solutions rely on vector databases, which store data based on semantic similarity. While effective for retrieval, they lack the nuance of how concepts connect. MemoriGraph distinguishes itself by leveraging knowledge graphs, built on the robust foundations of Neo4j and Graphiti. This approach transforms unstructured conversations and raw text interactions into a rich, structured graph that maps entities and their relationships. This allows the AI not just to recall data, but to understand the context and patterns behind that data.

Key Features and Capabilities

• Dynamic Evolution: The knowledge graph updates automatically as new interactions occur, ensuring the AI's memory grows alongside the user.
• Deep Contextual Understanding: By mapping relationships, the system can infer preferences and connections that linear vector searches miss.
• Open Source Flexibility: Developers have full control over the API, making it adaptable for various stacks and security requirements.

Perfect for Personalization

MemoriGraph is the ideal backend solution for applications requiring high levels of personalization. From recommendation engines that need to remember specific user tastes to digital assistants that recall past conversations with clarity, this tool provides the infrastructure for next-generation AI agents. By moving from flat memory to dimensional knowledge graphs, MemoriGraph enables applications that don't just process commands—they truly remember the user.