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RoofMaster Contractors — Roofing contractor, storm damage specialist

AI deployment blueprint for Roofing contractor, storm damage specialist. Automates roofing ops using Airtable, Google Maps, Twilio, Claude.

3 agents3 integrations50h freed/week2-3 weeks with Storm Lead Response Agent7h setupSimple

AI Readiness Score

72/100
RUN
data maturity65

Using Airtable suggests structured data approach, but may need cleanup for optimal AI performance.

team capacity70

Semi-technical team with existing Claude usage shows AI familiarity. Size suggests bandwidth for implementation.

budget alignment75

Budget range appropriate for proposed solution complexity and company revenue tier.

automation readiness80

Well-defined workflows in storm response and crew management. Clear pain points with measurable impact.

timeline feasibility68

3-6 month timeline realistic for phased implementation, though storm season urgency adds pressure.

integration complexity75

Excellent API ecosystem with Airtable, Google Maps, Twilio. All tools have robust APIs.

How This System Works

Architecture

Event-driven architecture leveraging existing tools (Airtable, Twilio, Google Maps) with Claude AI for intelligent processing. Storm leads trigger immediate response workflows, while scheduled optimization runs handle daily operations.

Data Flow

Customer inquiries flow through Twilio to instant response system. Job data accumulates in Airtable, feeding both documentation generation and crew optimization. All agents share the central Airtable database while specializing in specific operational areas.

Implementation Phases

1
Storm Response Foundation3-4 weeks

Implement immediate lead response to capture time-sensitive storm opportunities

Storm Lead Response Agent
2
Documentation Automation4-5 weeks

Automate insurance claim documentation to reduce administrative burden

Insurance Documentation Agent
3
Operations Optimization3-4 weeks

Implement crew scheduling optimization for daily operations efficiency

Crew Scheduling Optimizer

Prerequisites

  • -Airtable database cleanup and standardization
  • -Twilio webhook configuration
  • -Google Drive folder structure setup
  • -Crew skill matrix definition

Assumptions

  • -Storm season creates predictable lead volume spikes
  • -Insurance companies accept digital documentation packages
  • -Crew locations are tracked in real-time or updated daily
  • -Photo quality from field crews meets AI analysis requirements

Recommended Agents (3)

How It Works

  1. 1
    Receive storm damage inquiry

    Webhook captures SMS/voicemail with damage description and address

    Twilio
  2. 2
    Extract key information

    Parse damage type, urgency level, property address, contact info

    Claude
  3. 3
    Check crew availability

    Query current job assignments and crew locations

    Airtable
  4. 4
    Calculate response time

    Get drive time from nearest available crew to property

    Google Maps
  5. 5
    Send immediate response

    SMS with ETA, next steps, and emergency contact if urgent

    Twilio

Data Flow

Inputs
  • TwilioIncoming SMS/voicemail with damage details(JSON webhook)
  • AirtableCurrent crew schedules and locations(API response)
Outputs
  • TwilioImmediate response to customer with ETA(SMS)
  • AirtableNew lead entry with preliminary assessment(Record)

Prerequisites

  • -Twilio number setup
  • -Airtable crew tracking configured

Error Handling

warning
Unable to parse address

Flag for manual review and send generic response

info
No crews available

Send response with earliest availability and emergency contractor list

Integrations

SourceTargetData FlowMethodComplexity
TwilioAirtableSMS inquiries → Lead recordsapimoderate
Google MapsAirtableRoute optimization → Schedule updatesapimoderate
AirtableGoogle DriveJob data → Documentation packagesapilow

Schedule

0 20 * * *
Crew Scheduling OptimizerDaily at 8 PM to optimize next day's crew schedules
0 9,14 * * *
Insurance Documentation AgentProcess documentation queue twice daily

Recommended Models

TaskRecommendedAlternativesEst. CostWhy
Storm lead analysis and response generationClaude Sonnet 3.5
GPT-4
$30-40/monthExcellent at parsing unstructured damage descriptions and generating professional responses
Photo damage assessmentClaude Sonnet 4
GPT-4 Vision
$60-80/monthSuperior vision capabilities for identifying roofing damage patterns and materials
Route optimization logicClaude Haiku
GPT-3.5
$15-25/monthFast and cost-effective for mathematical optimization tasks

Impact

What Changes

Before
Manual lead response takes 4-8 hours, missing time-sensitive storm opportunities
After
Automated response within minutes, capturing more storm damage leads
Before
Insurance documentation takes 2-3 hours per job with frequent back-and-forth
After
Comprehensive documentation generated in 30 minutes with consistent quality
Before
Daily crew scheduling takes 45 minutes with suboptimal routing
After
Optimized schedules generated automatically with minimal manager review needed
Capacity Unlocked
Administrative staff can focus on customer service and business development instead of manual scheduling and documentation
Time to First Impact
2-3 weeks with Storm Lead Response Agent

Quality Gains

  • Consistent 1-hour storm lead response time
  • Standardized insurance documentation quality
  • Reduced crew travel time and fuel costs
50h freed up/week$260/mo estimated cost

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What's next?

This blueprint is a starting point. Fork it, remix it, or build your own.