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Memori Labs is an AI memory infrastructure platform that adds persistent, structured memory to AI agents and applications. It helps systems retain facts, preferences, rules, summaries, and conversation context across sessions, making it easier to build long-term memory into production workflows. The platform is designed to work with LLMs in a model-agnostic way and supports memory-backed retrieval across conversations and documents.
Key capabilities include automatic memory capture, targeted recall of relevant context, selective semantic search, and explainable results with lineage details showing why information was included. It also offers memory graph visualization, analytics for recall and usage, and controls for access, retention, deletion, and auditability. Developers can integrate it with existing databases or use the hosted cloud platform, depending on their setup and data ownership requirements. Memori Labs is positioned for use cases such as AI agents, support workflows, personalized experiences, and other applications that benefit from reliable long-term context.
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