Inspiration
Most hackathon demos over-promise intelligence without proving safety, auditability, or failure handling.
ReflexAI was inspired by the need to show how real-time AI systems should be structured first, before adding heavy inference.
What it does
ReflexAI is an event-driven safety intelligence prototype with a deterministic loop, explicit runtime policy control, real voice alerts, and append-only audit logs.
It demonstrates how decisions, policies, and side effects can be separated and verified.
How we built it
The system is built in Python using a LiquidMetal-style orchestration loop.
Decisions are triggered by state changes, passed through a runtime policy layer, and executed via non-blocking side effects such as logging, dashboards, and voice alerts.
A real ElevenLabs API integration generates voice alerts.
A web dashboard renders runtime JSON snapshots.
Challenges we ran into
Running reliable vision inference on CPU-only Windows hardware during a hackathon proved unstable.
To avoid false claims, perception input is explicitly mocked while preserving the system architecture.
Accomplishments that we're proud of
- A deterministic event loop with audit-grade logging
- Explicit policy gating with no silent API calls
- Real, verifiable voice alert generation
- Honest disclosure of mocked components
What we learned
Clear system boundaries and auditability matter more than feature count.
Honest prototypes build more trust than speculative demos.
What's next for ReflexAI — Event-Driven Safety Intelligence
- Wiring live vision inference into the decision loop
- CPU-validated ONNX/OpenCV pipeline
- Optional cloud persistence
Built With
- elevenlabs
- html
- javascript
- python
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