supermemory

supermemory provides a memory and continual learning system designed for agents. It maintains long-term memory of user interactions, documents, and events, and exposes this as profiles and memories that can be retrieved or used to augment models. The system is architecture-agnostic, working with any model or harness and hosted wherever the user needs it, including on premises.

The tool describes a workflow where data is ingested, memories are inferred and updated, and edges in a living graph connect memories across time. It emphasizes interoperability outside model providers so memory can accompany multiple model types and runtimes, with a focus on real-time context injection into model prompts.

The product highlights a research-backed memory graph, timeline-aware facts, and a retrieval flow designed for agent loops. It includes features such as recall, hybrid search, and multimodal extraction, all aimed at providing structured, time-aware memory for AI agents.

It mentions SOC 2, HIPAA, GDPR alignment, and a customer-focused support structure.

Use cases

• Maintain long-term memory per user or tenant to power contextual AI assistants