#AI memory
3 tools curated for you
Eliminate repetitive queries and redundant processing through semantic memory clustering that identifies and recalls similar past interactions Build chatbots that resolve queries faster by remembering past conversations and relevant context from previous interactions Develop AI that evolves with user preferences by recalling and learning from historical interactions to adjust responses over time Create autonomous systems that grow smarter with each engagement through continuous learning from interaction data Deliver personalized retail recommendations by remembering individual customer purchase histories and preferences Reduce AI hallucinations and improve response accuracy through context-aware retrieval from both short-term and long-term memory layers Optimize memory usage and maintain focus on current priorities with intelligent memory decay that removes outdated information Integrate seamlessly with existing AI platforms like OpenAI and Ollama without disrupting your current workflow
Eliminate AI tool silos and maintain a single source of truth across Cursor, Claude, and other agents via the Model Context Protocol (MCP) without custom integrations Automatically keep knowledge current with scheduled autonomous jobs that detect drift and update facts from GitHub, Google Drive, and docs hourly or daily Enable AI agents to reason like a senior team member by traversing chains of decisions using a graph memory with typed edges (depends_on, owned_by) Retrieve precise answers under tight context windows using hybrid retrieval that combines semantic vector search with structured graph traversal Preserve data sovereignty and keep proprietary context secure with self-hosting options and workspace isolation, without storing raw file copies Maintain full governance and traceability with comprehensive audit logs that back every fact to its source and use scoped API keys
Eliminate AI knowledge silos by building a single, persistent source of truth that any AI tool can access, powered by centralized AI-ready databases called Brains. Maintain full data sovereignty and control with enterprise-grade guardrails, usage auditing, and the option for on-premises deployment to protect sensitive information. Infuse AI assistants in Microsoft Teams and other MCP-compatible apps with real-time organizational knowledge, providing instant access to product details and FAQs. Understand complex relationships within your data beyond simple document links using GraphRAG technology for deeper, more contextual AI insights. Monetize internal expertise or tap into external knowledge by buying and selling specialized Brains through the integrated Brain Marketplace. Audit and govern all AI interactions across your organization from a central dashboard, tracking usage, costs, and ensuring policy compliance.