AI Readiness Score
Structured risk data in HubSpot, established questionnaire formats
Small team but existing Claude usage shows AI comfort level
Budget supports comprehensive automation for high-impact processes
Well-defined processes with clear decision trees for risk assessment and policy binding
3-6 months reasonable for phased implementation
HubSpot API available, but may need custom email parsing and document management
How This System Works
Architecture
Event-driven system centered around HubSpot CRM with email monitoring, document automation, and real-time notifications via Slack
Data Flow
Applications flow from HubSpot through risk analysis, policy binding automation, and ongoing claims monitoring via email surveillance
Implementation Phases
Implement automated risk scoring and questionnaire analysis
Streamline document generation and approval workflows
Deploy proactive claims detection and notification system
Prerequisites
- -HubSpot admin access
- -Gmail API permissions
- -Document template standardization
- -Claims workflow documentation
Assumptions
- -Questionnaires follow consistent format
- -Email-based communication with insureds
- -HubSpot as single source of truth for policies
Recommended Agents (3)
How It Works
- 1Detect new questionnaire submission
Monitor for new deals with 'Risk Assessment' stage
HubSpot webhook - 2Extract and parse questionnaire data
Process PDF/form responses into structured data
Claude API - 3Analyze risk factors against database
Score industry, revenue, security posture, claims history
Custom risk engine - 4Generate risk report and recommendations
Create standardized risk summary with coverage recommendations
Claude API - 5Update HubSpot with results
Add risk score, notes, and next actions to deal record
HubSpot API
Data Flow
Inputs
- HubSpot — Deal records and questionnaire attachments(JSON)
- Email — Completed risk questionnaires(PDF/DOC)
Outputs
- HubSpot — Updated deal with risk score and analysis(JSON)
- Slack — Risk alert notifications for high-risk applications(Message)
Prerequisites
- -HubSpot API access
- -Document parsing capability
- -Risk scoring framework
Error Handling
Flag for manual review with error details
Use cached data and notify admin
Integrations
| Source | Target | Data Flow | Method | Complexity |
|---|---|---|---|---|
| HubSpot | Risk Assessment Analyzer | Deal records and questionnaires | webhook | moderate |
| Gmail | Claims Monitor | Incoming emails from insureds | api | high |
| Risk Analyzer | Policy Binding Agent | Approved risk assessments | direct | low |
| All Agents | Slack | Notifications and alerts | webhook | low |
Schedule
*/15 * * * *0 9,13,17 * * 1-5Recommended Models
| Task | Recommended | Alternatives | Est. Cost | Why |
|---|---|---|---|---|
| Risk questionnaire analysis | Claude Sonnet 3.5 | GPT-4 | $80/month | Complex reasoning required for risk assessment with high accuracy needs |
| Document generation | Claude Haiku | GPT-3.5 | $40/month | Template-based generation with fast response requirements |
| Claims incident detection | Claude Sonnet 3.5 | GPT-4 | $90/month | Critical accuracy for incident classification to prevent false positives |
Impact
What Changes
Quality Gains
- ✓Consistent risk assessment scoring reduces underwriting errors
- ✓Faster claims response improves customer satisfaction and reduces disputes
- ✓Automated policy binding reduces processing errors
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What's next?
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