Sentinel Climate

Decision support for climate emergencies. Sentinel Climate watches public data feeds for climate disruption — extreme heat, flash floods, grid stress, dirty air — scores the risk to a specific county, and drafts a resource-allocation plan against that county's real inventory: cooling centers, ambulances, high-water vehicles, medical teams. The mission is timing: get the right resources moving toward the right place before the disaster peaks, not after.

It is decision support, not decision making. Every assessment ends with a recommendation that a human emergency manager must review before anything deploys. That constraint is wired into the data model, not the marketing.

How it works

  OSINT sources                     Multi-agent pipeline
 ┌──────────────┐                 ┌──────────────────────────┐
 │ NWS alerts   │                 │  SENTINEL  hazard watch  │
 │ USGS gauges  │   ┌─────────┐   │  MEDIC     health risk   │   ┌────────────┐
 │ OpenFEMA     │──▶│collector│──▶│  DISPATCHER logistics    │──▶│ allocation │
 │ EIA grid     │   │(snapshot│   │  COMMANDER decision      │   │   engine   │
 │ AirNow AQI   │   │ + prov- │   ├──────────────────────────┤   └─────┬──────┘
 │ CDC heat     │   │ enance) │   │ Claude (ANTHROPIC_API_   │         │
 └──────────────┘   └─────────┘   │ KEY) or deterministic    │         ▼
                                  │ rules fallback           │   ┌────────────┐
                                  └──────────────────────────┘   │ dashboard  │
                                                                 └────────────┘

1. Collector pulls a fresh snapshot of a county from public OSINT feeds and records, per source, whether the data was live, degraded, or unavailable.
2. Multi-agent pipeline — four agents in sequence: SENTINEL reads the hazards, MEDIC assesses population health risk, DISPATCHER works the logistics, COMMANDER makes the call (MONITOR / DEPLOY / EMERGENCY). With an ANTHROPIC_API_KEY the agents run on Claude; without one, a deterministic rules engine produces the same report shape and says so.
3. Allocation engine converts the risk score into resource demand, fills it from the county's inventory, and reports every shortfall with a mitigation — it never pretends inventory it doesn't have.
4. Dashboard renders the assessment with the provenance of every input.

Data sources

Source	What	Key required	Status when unconfigured
NWS (api.weather.gov)	Weather alerts, forecasts, heat index	None	Live
USGS Water Services	River gauge height and discharge	None	Live
OpenFEMA	Disaster declarations	None	Live
EIA	Grid demand and reserve margin	EIA_API_KEY	Unavailable (labeled)
AirNow	Air quality index	AIRNOW_API_KEY	Unavailable (labeled)
CDC	Heat-health data	CDC_API_KEY	Unavailable (labeled)
Google CSE + OpenAI	Social listening / OSINT sweeps	GOOGLE_CSE_API_KEY, GOOGLE_CSE_ID, OPENAI_API_KEY	Unavailable (labeled)
ElevenLabs / Twilio	Voice and SMS outreach	ELEVENLABS_API_KEY, TWILIO_*	Demo mode (simulated, labeled)

All keys are optional and free to register. The app runs with zero keys — it just tells you, per source, that it is running degraded.

Quickstart

cp env.example .env    # fill in whichever keys you have; all are optional
npm install
npm run dev

Open http://localhost:5001. The server reads PORT from the environment and defaults to 5001 — port 5000 collides with AirPlay Receiver on macOS, so set PORT explicitly if you need a different one.

Checks:

npm run check   # TypeScript, strict mode
npm test        # vitest — allocation engine, rules engine, county registry

Data honesty

The core product rule: simulated data is never presented as live.

• Every assessment carries per-source provenance — a SourceStatus for each feed stating live, degraded, or unavailable, with a timestamp. The dashboard renders these as a provenance strip on every result.
• Every agent report is stamped with its mode: ai (Claude, model id included) or rules (deterministic fallback). The fallback never masquerades as AI.
• In rules mode, agent confidence is the fraction of data sources that were actually live — measured, not invented.
• Every decision output sets reviewRequired: true. A qualified human reviews before any resource moves. There is no auto-deploy path.

Origin

Built at the AI+ Expo hackathon in June 2025, now being hardened into a real decision-support tool: typed contracts shared between server and client, a deterministic fallback for every AI path, provenance on every payload, and tests on the allocation math.