Case studyRidge
The storm hits.
The pipeline fills.
Ridge runs the whole roofing operation. It detects hailstorms, maps the affected zones, finds the homeowners inside them, reaches out automatically — then schedules the inspections and dispatches the crews. One platform, storm to signed job.
Radar active
Plano, TX→ mapped
Frisco, TX→ mapped
Outreach run→ sent
Allen, TXwatch
Job scheduled→ booked
McKinney, TX→ mapped
roofs mapped today 6,420leads 1,180
# EngagementRoofing ops platform
# RoleDesign → deploy
# StackReact · Python
# ModelsGemini multi-model · Qwen
# IntegrationsWeather · property · comms
# SurfaceMulti-tenant SaaS
# 01 /The problem
After the hail,
it's a race.
When a hailstorm hits, thousands of roofs need work and the first roofer to the door wins. But finding the affected streets, matching them to homeowners, and reaching out fast enough is manual, scattered across tools, and slow — so the leads go cold.
Ridge turns a storm into a routed, scheduled pipeline — in minutes.
# 02 /What we built
Storm to signed job.
One pipeline.
A single system carries a weather event all the way to a dispatched crew — detect, map, identify, reach out, schedule, and assign, without leaving the platform.
01DetectHail & storm cells
02ZonesRegions mapped
03IdentifyRoofs & owners
04OutreachMultichannel
05ScheduleJobs booked
06DispatchCrews assigned
# 03 /How it works
A storm cell in. A ready pipeline out.
Weather and property feeds combine into a live picture of every affected zone. Ridge ranks them, matches roofs to owners, and stages outreach — so a crew is knocking while competitors are still pulling maps.
- Detects and ranks hail zones by damage and roof density.
- Matches roofs to owners via property-data integrations.
- Stages outreach, then schedules and dispatches crews.
# 04 /Architecture
Four layers.
Field-ops to AI.
A React workspace for the team, a Python operations API, a multi-model AI core, and a web of third-party weather, property, and communications integrations.
L1WorkspaceReact · Next.jsOps console, CRM, scheduling board, and crew assignment.
L2Operations APIPythonStorm ingestion, zone mapping, lead matching, outreach, and dispatch.
L3AI modelsGemini (multi-model) · QwenZone analysis, lead scoring, outreach copy, and damage-photo understanding.
L4IntegrationsWeather · property · commsHail/storm feeds, property & owner records, SMS / email / voice.
# 05 /Results
The numbers
after the storm.
What storm-driven operations look like once the whole pipeline runs on one platform.
0%
of affected roofs identified and matched to owners after a storm event.
0×
more qualified leads per storm than door-to-door canvassing.
<0min
from storm detection to a mapped outreach list — not days of manual research.
0
platform for the whole operation — leads, outreach, scheduling, and crews.
↳ Illustrative figures — replace with audited numbers before publishing.
# 06 /Capabilities
What Ridge ships with.
Everything a roofing company needs to turn the next hailstorm into booked, dispatched work.
# 01Storm & hail detection
Ingests live weather data to pinpoint hail events the moment they land.
weather · hail
# 02Weather-zone mapping
Draws affected regions and ranks them by hail size and roof density.
zones · rank
# 03Lead identification
Matches roofs inside a zone to property and owner records automatically.
match · owners
# 04Automated outreach
Multichannel campaigns — SMS, email, and mail — to homeowners in the zone.
sms · email
# 05Scheduling & dispatch
Books inspections and assigns internal crews to jobs on a live board.
jobs · crews
# 06Client & CRM management
Tracks every homeowner from first contact through a completed roof.
crm · pipeline
# Engage
Let's talk growth.
30-minute scoping call. You leave with a written scope and a target ship date — or with an honest “we're not the right firm.”