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glamor shot
Autonomous Network Operations Commander with voice streaming capability -
A live AI operations engineer for enterprise incidents.
- Cisco enterprise problem framing
- VoiceOS
- Redis state/memory
- GetStream collaboration
- Tencent Cloud infra
- AdaL agents
- ButterBase structured memory/data
A simulated enterprise outage
Example:
“Branch office lost connectivity.”
The system:
- detects the incident
- launches AI investigation agents
- speaks to engineers via voice
- streams remediation updates live
- remembers prior outages
- generates incident timeline
- proposes fix actions
| Sponsor | Use |
|---|---|
| Redis | agent memory, event bus, incident state |
| VoiceOS | real-time voice operations assistant |
| AdaL | multi-agent orchestration |
| ButterBase | incident knowledge graph + memory |
| GetStream | live team collaboration/chat feed |
| Tencent Cloud | deployment + inference infra |
| Cisco | enterprise/network/security use case |
AI should run incident response.
- AI Site Reliability Engineer
- AI NOC operator
- AI incident commander
The AI should feel like:
- a teammate
- a command center operator
- an autonomous system
Architecture
Frontend
- Next.js
- Tailwind
- Stream-style dashboard UI
Backend
- FastAPI or Node
- Redis pub/sub
- agent orchestrator
AI Layer
- AdaL multi-agent workflows
- OpenAI or Claude
Voice
- Hypescribe + VoiceOS realtime interaction
Persistence
ButterBase for:
- incidents
- memory
- topology
- remediation history
Live Collaboration
- GetStream channels
- incident chat
- agent logs
Features
1. Live Voice Agent
2. simulated Multi-Agent Incident Investigation
3. simulated Live Streaming Incident Feed
4. simulated Redis Event Bus
5. Cisco-style Enterprise Dashboard
If we survive into final judging:
We plan to add:
- memory across incidents
- autonomous remediation simulation
- topology graph
- root cause prediction
- severity scoring
- incident replay timeline
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