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Here's the README — output exactly as requested, no fences:


MaulDocket

The only claims platform built specifically for when the dog bites back.

MaulDocket handles the full lifecycle of animal attack insurance claims from incident intake through final settlement, with breed-specific actuarial tables baked in. It cross-references local dangerous-animal ordinances, prior bite history registries, and homeowner policy data to produce defensible liability scores in under 30 seconds. Insurance adjusters who've demoed it describe the experience as "deeply unsettling but the fastest I've ever closed a file."

Features

  • Full incident-to-settlement claim lifecycle management with zero dropped handoffs
  • Breed-specific actuarial engine covering 312 recognized and unrecognized breeds, updated quarterly
  • Live cross-reference against municipal dangerous-animal ordinance databases via ClaimsBridge API
  • Automated prior bite history lookups across 47 state registries. In real time.
  • Defensible liability scoring with exportable audit trails built for courtroom use

Supported Integrations

Salesforce, Guidewire ClaimCenter, ISO ClaimSearch, LexisNexis Risk Solutions, ClaimsBridge, VetTrack Registry, BiteLogix, Verisk A-PLUS, Stripe, DocuSign, MuniciCode Direct, NeuroSync Underwriting

Architecture

MaulDocket is built on a microservices backbone with each domain — intake, scoring, ordinance lookup, and settlement — running as an independently deployable service behind an internal API gateway. The actuarial engine is written in Go for throughput reasons that will become obvious the first time you run a batch of 10,000 claims. All claim state is persisted in MongoDB because the document model maps cleanly to the irregularity of real-world incident data, and Redis handles the long-term breed-registry cache that keeps ordinance lookups fast. Every service logs to a centralized pipeline and I have never once lost a claim record.

Status

🟢 Production. Actively maintained.

License

Proprietary. All rights reserved.

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