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Supermemory is an open source memory API for AI applications that stores, indexes, and retrieves user-specific context so LLMs can deliver personalized responses across sessions. Apache-2.0 licensed.
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Supermemory is an open source memory API for AI applications that stores, indexes, and retrieves user-specific context so that LLMs can deliver personalized responses without building a custom RAG pipeline from scratch.
LLMs have no memory between conversations by default. Building long-term memory for AI applications requires designing a storage layer, an embedding pipeline, a vector search retrieval system, and a context injection mechanism. Doing this correctly for each new application is weeks of engineering work, and doing it poorly produces retrieval that is slow, imprecise, or returns irrelevant context.
Supermemory provides a REST API that accepts memory entries (text, documents, web content), embeds them, and stores them in a vector database. When an LLM needs context, the application queries Supermemory with the current user ID and topic, and Supermemory returns the most relevant memories ranked by semantic similarity. Apache-2.0 licensed; self-host via Docker.
Supermemory is best for developers building personal AI assistants, customer-facing AI agents, or knowledge management applications who want a pre-built memory layer rather than assembling embedding pipelines and vector retrieval from scratch.
Unlike Mem0, Supermemory is fully open source under Apache-2.0 and designed for self-hosting with no cloud dependency. Mem0 offers a managed service with additional memory management features and integrations; Supermemory gives full control over memory storage and retrieval at no variable cost.
