📈 Live history is activating for this object — the automated backfill is in progress.
⌁ mcp.call("adw-395") v1.0 High grid stress during heatwaves in UHI zones predicts localized transformer failures and disproportionate maintenance costs.
📈 Live history is activating for this object — the automated backfill is in progress.
⌁ mcp.call("adw-395") v1.0 Built from our 2,700+ data feeds and validated against a naive baseline before release.
Version 1.0 · validated to beat a naive baseline · benchmark: —
One call returns the answer with its reasoning attached — the live Intelligence Object for ADW-395.
{} Every product conforms to the Intelligence Object Model — typed, versioned, and discoverable.
Dashboard
Read the score + drivers in the console.
REST API
/v1/intelligence/adw-395
MCP tool
adw.adw_395
Marketplace
Discoverable by any MCP agent via the MCP registry.
White-label
Embed under your own brand (Platinum).
Enable organizations to prioritize and allocate capital expenditure for climate resilience projects based on quantified physical risk exposure.
Method: Aggregate geospatial hazard data (flood, fire, heat) with asset location and value inputs to calculate a risk-adjusted return on investment score for each potential adaptation intervention.
Are US climate-disaster costs trending above historical norms?
Method: z-score of latest annual cost vs full 1980-present history → clamp(50 + z×15, 0, 100)
How heavy is the current US severe-weather alert load?
Method: Severity-weighted (Extreme4/Severe3/Moderate2/Minor1) active-alert sum, scaled