Guides, tutorials, and deep dives on AI memory for LLMs and agents.
Learn what AI memory is, why LLMs need it, and how persistent memory transforms stateless chatbots into context-aware agents.
ComparisonArchitectureRAG retrieves documents. AI memory learns from interactions. Understand when to use each and why the best agents use both.
Deep DiveFundamentalsUnderstand the three types of memory that make AI agents truly intelligent: semantic (facts), episodic (events), and procedural (workflows).
TutorialQuick StartStep-by-step tutorial to add persistent memory to any AI agent using Python or JavaScript. Works with OpenAI, Anthropic, and any LLM.
FeatureDeep DiveCognitive Profile generates a complete system prompt from a user's memory history. One API call turns scattered memories into a personalized context block.
TutorialMCPConnect Mengram's AI memory to Claude Desktop via MCP. 12 tools for search, add, profile, and more — setup in under 3 minutes.
ComparisonBenchmarkDetailed feature-by-feature comparison of Mem0 and Mengram for AI agent memory. Pricing, memory types, API design, and performance benchmarks.
TutorialIntegrationAdd long-term memory to CrewAI and LangChain agents with Mengram. Code examples for both frameworks with semantic, episodic, and procedural memory.