Same architecture. Infinite configurations. Memory that persists changes everything.
We showed you seven use cases. But the truth is — persistent, local, emotionally-aware AI memory isn't built for one purpose. It's a fundamental shift in how AI works. Every tool that currently resets every conversation, forgets your context, and sends your data to a cloud is a tool that could be rebuilt on this architecture. The problem isn't any single use case. The problem is that AI has been stateless by default, and we think that's wrong.
The architecture is the same across every use case. Hybrid memory — keyword, semantic, and importance scoring. Emotional state that carries across sessions. Memory connections that link related moments by type and weight. Autonomy between interactions. Full local execution with no cloud dependency. What changes isn't the engine. What changes is what you point it at. Memory that persists isn't a feature. It's a foundation. Build whatever you want on top of it.
Same architecture. Different purpose. The core is memory that persists.
See other use cases