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Persistent memory for agentic AI

Give AI systems memory that lasts.

HumemAI gives AI systems a memory layer that stays persistent across sessions, adapts to mixed data types, and remains inspectable instead of turning into a black box.

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How HumemAI worksGUI + hosted + API-ready

Episodic memory

Capture what happened, when it happened, and why it matters across interactions.

Semantic memory

Keep documents, tables, graphs, and connected systems in the most useful structure.

Hybrid retrieval

Let agents query relationships, vectors, and structured knowledge in one memory layer.

Product

Built for real agent workflows

See how HumemAI handles conversational history, structured knowledge, and hybrid retrieval in one system.

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Pricing

Open source or hosted

Developers can self-host from GitHub. Teams that want outcomes can use a managed deployment.

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Projects

Research and projects in public

Follow the projects that shaped HumemAI so far, from audit-ready memory systems to embedded database work.

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Why now

Agents still forget.

The world is getting more agentic, but most systems remain stateless chat wrappers. HumemAI focuses on the missing layer: persistent, explainable memory that agents can use over time.

  • Persistent memory across sessions instead of stateless chat
  • Support for documents, tables, graphs, and connected data
  • Open-source foundations with a hosted product path
  • Explainable memory structures that teams can inspect and control