AI Readiness Score
Claims data is structured but vet records vary in format. Historical data available for training models.
Startup team is agile and tech-savvy. Limited dedicated AI/automation resources but high motivation.
Budget range supports automation initiatives. Strong ROI potential from claims processing efficiency.
Claims processing is highly structured and rule-based, perfect for automation. Clear decision trees exist.
3-6 month timeline is realistic for phased rollout. Claims automation can show quick wins.
Existing tools have good APIs. Supabase provides unified data layer. Some vet system integrations needed.
How This System Works
Architecture
Event-driven automation system using Supabase as central data hub, Claude for AI analysis, and existing tools for execution. Claims flow through validation and review pipelines with human oversight for complex cases.
Data Flow
Claims enter through Supabase, trigger ClaimsReviewAgent for initial analysis. VetRecordValidatorAgent processes supporting documents. DynamicPricingAgent calculates premiums for new policies. All agents update central database and trigger appropriate notifications through Twilio.
Implementation Phases
Automate routine claim processing and approval
Add automated vet record verification
Implement dynamic pricing model
Prerequisites
- -Supabase schema optimization for claims data
- -Claude API integration setup
- -Claims processing rules documentation
- -Historical data cleanup and preparation
Assumptions
- -Current claims volume: 200-300 per month
- -Average claim processing time: 45-60 minutes
- -70% of claims are routine and automatable
- -Existing team available for training and oversight
Recommended Agents (3)
How It Works
- 1Receive claim notification
Webhook fires when new claim record created
Supabase - 2Extract claim details
Fetch policy info, vet records, invoice data
Supabase API - 3Analyze claim validity
Check against policy terms, verify treatment codes, assess documentation
Claude - 4Calculate coverage amount
Apply deductibles, co-pays, and benefit limits
Claude - 5Update claim status
Mark as approved, denied, or needs review with reasoning
Supabase API - 6Notify stakeholders
SMS/email to customer and internal team
Twilio
Data Flow
Inputs
- Supabase — Claim details, policy info, vet records(JSON)
- File uploads — Vet invoices and medical records(PDF/Images)
Outputs
- Supabase — Updated claim status and review notes(JSON)
- Twilio — Notifications to customers and staff(SMS/Email)
Prerequisites
- -Structured claims data schema
- -Policy rules codification
Error Handling
Flag for human review
Retry with exponential backoff
Auto-deny with explanation
Integrations
| Source | Target | Data Flow | Method | Complexity |
|---|---|---|---|---|
| Supabase | Claude | Claims data for analysis | api | low |
| Claude | Supabase | Analysis results and decisions | api | low |
| Supabase | Twilio | Notification triggers | webhook | low |
| DynamicPricingAgent | Stripe | Premium calculations for billing | api | moderate |
Schedule
0 6 * * **/15 * * * *Recommended Models
| Task | Recommended | Alternatives | Est. Cost | Why |
|---|---|---|---|---|
| Claims analysis and decision making | Claude Sonnet 4 | GPT-4 | $200-300/month | Excellent reasoning for insurance logic, good at following complex rules |
| Document OCR and validation | Claude Sonnet 4 | GPT-4 Vision | $150-200/month | Strong vision capabilities for document analysis and fraud detection |
| Pricing calculations | Claude Sonnet 4 | GPT-4Claude Haiku | $100-150/month | Mathematical reasoning and actuarial analysis capabilities |
Impact
What Changes
Quality Gains
- ✓Consistent claims evaluation criteria
- ✓Faster customer response times
- ✓Reduced pricing errors and disputes
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What's next?
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