# no-signal

- **Event:** [Google DeepMind Bangalore Hackathon](https://cerebralvalley.ai/e/google-deepmind-bangalore-hackathon)
- **When:** Sat, Jul 11 at 9:00 AM – 10:00 PM (GMT+5:30)
- **Where:** Marathahalli, Marathahalli Main Road
- **Placement:** Finalist
- **Team:** [Ajay Agrawal](https://cerebralvalley.ai/u/ajayagrawal), [Aloys Jehwin](https://cerebralvalley.ai/u/aloysjehwin)
- **GitHub:** https://github.com/AloysJehwin/no-signal/
- **Demo video:** https://youtube.com/shorts/q5hbmABh020
- **Gallery:** https://cerebralvalley.ai/e/google-deepmind-bangalore-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/google-deepmind-bangalore-hackathon/hackathon/gallery/15

True Autonomous, Offline-First Multimodal Diagnostic Agent

1. Real-Time Multimodal Interaction (Gemini Live)
Most "voice assistants" are just text interfaces wearing a microphone—wait, process, respond, repeat. no-signal breaks this rigid turn-based structure. Leveraging the Gemini Live API and Gemma Multimodal, the agent can see what the technician sees through a live camera feed and listen to real-time audio. Users can interrupt the agent mid-response, the model reads vocal tone, and it proactively points out anomalies in the video feed that the user hasn't explicitly mentioned. It’s a fluid, uninterrupted collaboration, not a staggered Q&A.

2. True Local-First Agency (Gemma 4 On-Device)
Most "on-device AI" simply moves a cloud chatbot onto a phone. It forgets context, fails rigidly, and assumes a server connection will eventually return. Real agency means holding state across a complex diagnostic task, deciding what to do next based on what’s already been learned, and recovering when a plan breaks—entirely offline.

Across regions with spotty connectivity, sending data to a server is a non-starter. no-signal runs a complete, autonomous Sense → Decide → Act → Check loop entirely on-device using Gemma 4. It isn't a straight arrow from input to output. It maintains local state, attempts a fix, evaluates if the fix worked, revises its hypothesis upon failure, and knows exactly when to draw a boundary and defer to a human.

3. Fleet-Wide Continuous Learning
When the local agent hits a dead end, it caches the unresolved session. The moment the device reconnects to the internet, our orchestration pipeline syncs the session to the cloud. Gemini Flash conducts web-grounded research to find the fix, Nano banana generates visual guides, and Gemini Flash Live synthesizes real-time audio instructions. This new knowledge is distilled into a structured fault-tree and instantly pushed back to the local device. The next time any technician faces the issue offline, Gemma 4 resolves it instantly.

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Markdown version of https://cerebralvalley.ai/e/google-deepmind-bangalore-hackathon/hackathon/gallery/15. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt