

Mengram provides AI memory capabilities with three distinct memory types modeled after human brain architecture: semantic memory for facts and preferences, episodic memory for events and discussions, and procedural memory for workflows and processes. The system automatically extracts these memory types from conversations and interactions, creating a comprehensive memory system for AI applications.
The key features include Cognitive Profile generation that creates ready-to-use system prompts from all three memory types, unified search across semantic, episodic, and procedural memories using vector + BM25 + graph expansion + LLM re-ranking, and autonomous memory agents including Curator for cleaning contradictions, Connector for finding hidden patterns, and Digest for weekly briefs. Additional capabilities include procedure feedback with success/failure tracking, team memory sharing with invite codes, webhooks for memory change notifications, knowledge graph representation of entities and relations, AI reflections generating behavioral insights, and smart triggers for proactive memory alerts.
The system works by connecting to AI tools via MCP (Model Context Protocol) or API, automatically extracting the three memory types from conversations, and providing unified access through a single API call. It offers drop-in integrations with popular frameworks including LangChain, CrewAI, and OpenClaw, allowing developers to replace existing memory systems with minimal code changes.
Benefits include instant personalization for any LLM through Cognitive Profiles, replacement of complex RAG pipelines with a single API endpoint, and autonomous learning capabilities where AI agents complete tasks and Mengram saves the steps so future interactions already know optimal paths with success tracking. Use cases span AI assistants that remember user preferences and workflows, development tools that learn optimal coding patterns, and customer support systems that maintain context across conversations.
The product targets developers building AI applications, AI agent frameworks, and teams requiring persistent memory across AI interactions. It integrates with Claude Desktop via MCP server, provides Python and JavaScript SDKs, and offers framework-specific integrations for LangChain, CrewAI, and OpenClaw. The system is self-hostable and operates with both cloud and local deployment options.
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Mengram targets developers building AI applications, AI agent frameworks, and teams requiring persistent memory across AI interactions. It serves users of Claude Desktop, Cursor, Windsurf, ChatGPT, LangChain, CrewAI, OpenClaw, and Perplexity who need their AI systems to maintain context and learn from interactions. The product is designed for technical users who want to replace complex RAG pipelines with a simpler memory solution and teams looking to share AI memory knowledge across members.