Wherobots MCP Series: Property-Level Climate Risk Scoring for Insurance

Which properties in your target ZIP codes carry the highest compound climate risk?

Watch us score thousands of residential properties for wildfire, flood, and building risk in a single live session, using natural language queries against real datasets, all from VS Code.

What this session covers

We’ll tackle one of the most time-consuming questions in underwriting: compound property risk at scale. Using the Wherobots MCP in VS Code, we go from a natural language question to a weighted risk model, a scheduled monthly pipeline, and a live risk heatmap, without leaving the editor.

The datasets are already in the Wherobots catalog: 2M+ wildfire records, Regrid parcels with FEMA flood zones and building valuations, and Overture buildings with roof material and height. No data wrangling setup. No waiting.

Agenda

• 5 min — Context and business question setup
• 25 min — Live MCP demo: natural language queries, catalog exploration, weighted risk model build (wildfire proximity 40%, flood zone 30%, building age 20%, roof material 10%)
• 5 min — Scheduling the model as a monthly production job
• 8 min — Vibe-coding a risk heatmap: properties colored green to red by score, with clickable popups showing component breakdowns
• 10 min — Q&A

What you will walk away with

A clear picture of how to score compound property risk across large portfolios using spatial data that is already structured and ready to query. The same model runs as a scheduled job, so your risk scores stay current as new wildfire and flood data comes in.

Bonus for attendees

Sign up for a Pro trial within 7 days of attending and get a free 30-minute 1-on-1 session with a Wherobots spatial data engineer to adapt this demo to your data.

Who should attend

Underwriting teams, climate risk analysts, reinsurance modelers, and insurtech engineers who need property-level risk scores at scale without building the data infrastructure from scratch.