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AI Risk ResearchIndependent monitoring and live experiments
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Built for Meta's Global AI Developer Hackathon

Indie track / local and cloud coordination

Handoff

A test bench for deciding when work should stay on a local model, move to a cloud model, or return with a compact verified result.
01

Keep private work local

Local models handle sensitive context, quick classification and tasks that should not leave the device.

02

Escalate deliberately

Cloud models receive only the minimum approved context when a task needs deeper reasoning or broader capability.

03

Verify every boundary

Each transfer records routing, latency, quality and risk flags without publishing prompts, private data or hidden reasoning.