# Sentinel

- **Event:** [Google I/O Hackathon](https://cerebralvalley.ai/e/google-io-hackathon)
- **When:** Sat, May 23 at 9:00 AM – 10:00 PM (PDT)
- **Where:** Shack15, San Francisco, CA
- **Team:** [Rich Lira](https://cerebralvalley.ai/u/richlira)
- **GitHub:** https://github.com/richlira/sentinel
- **Demo video:** https://www.tella.tv/video/richs-video-5sj5
- **Gallery:** https://cerebralvalley.ai/e/google-io-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/google-io-hackathon/hackathon/gallery/51

Sentinel is an agentic privacy-routing system: sensitive data never leaves your hardware, yet the cloud still gets useful work done. A Google Managed Agent ingests a document and, before reading a single raw byte itself, delegates the un-redacted content to a Gemma model running locally on the operator's NVIDIA DGX Spark (via Ollama behind an allowlisted tunnel). The local model classifies and masks every sensitive span (PII / financial / medical); the cloud agent then reasons only over the masked output and produces a PDF report plus an audit-log.json that proves, line by line, what touched cloud vs. local. The headline guarantee — verified end-to-end — is raw_sensitive_bytes_processed_in_cloud: 0. The problem it solves: organizations want cloud-scale AI but can't legally or ethically expose raw PII to it. Sentinel makes "the cloud trusts the local model's answer without ever seeing the raw data" an enforceable, auditable boundary rather than a policy promise.

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Markdown version of https://cerebralvalley.ai/e/google-io-hackathon/hackathon/gallery/51. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt