Aether

Aether is a modular assistant runtime for local-first AI execution. Status: In Development. Current scope includes memory layers, voice interaction, skill execution, plugins, scheduler jobs, structured logs, validation flows, and dashboard pages.

Context

Most AI assistants are cloud-bound, stateless, and disconnected from local tools with limited visibility into internal state.

Approach

Aether uses modular local runtime services: memory layers, voice support, plugin registries, skill execution, scheduled jobs, structured logs, validation flows, and dashboard pages.

Features

Voice support

Memory layer

Plugin registry

Skill execution

Scheduler

Dashboard status pages

Capabilities

• Modular assistant runtime architecture in development
• Local-first execution as the core design constraint
• Voice interaction workflows on the build roadmap
• Memory and knowledge-base layers under design
• Plugin and skill execution as planned modules
• Scheduler jobs and dashboard pages for runtime visibility

Technologies

PythonFastAPILocal modelsSQLiteSchedulerStructured logs

Notes

• Runtime base for persistent local assistants.
• Dashboard and log pages expose scheduler and memory state.

Contact

Contact Projects