I built a fully local voice-first autonomous Al agent for Windows
Rika is a fully autonomous, sovereign, voice-first personal AI agent built from scratch. Runs entirely locally on Windows, boots with the system, operates as a persistent background intelligence.
What she does:
* Wake word activation, sub-300ms voice-to-response
* Sees the screen via 3-tier targeting (Windows Accessibility, RapidOCR, Pixtral)
* Ghost-types into any application by voice (code, emails, documents)
* Six-layer persistent memory with midnight consolidation
* Multi-agent swarm (concurrent background agents)
* Full Telegram remote control from phone
* Full-duplex interruption (stops mid-syllable when you speak)
* Emotion-reactive UI (interface shifts color based on state)
* Custom neural voice (`rika.pt` tensor, 3-way blend)
* Self-evolving (reads docs, writes her own integration code)
* Real-time data interception (zero-latency feeds injected into context)
The part nobody talks about:
Everyone obsesses over the LLM call. The actual bottleneck is everything around it. I spent more time debugging audio buffer sizes for interruption latency than I did on the entire memory architecture. And the midnight daemon that consolidates her memories? First 3 versions just hallucinated fake memories. Had to build an adversarial staleness detector that cross-checks new summaries against raw interaction logs before writing anything permanent.
GitHub: https://github.com/nssriraam/rika
Ask me anything!