Most carrier AI dies in pilot. Ours doesn't — because we build for the production day, the audit day, and the day a regulator asks why a model declined a referral. Claims triage, underwriting decisioning, intelligent document processing, agentic operations, producer portals.
Severity scoring, fraud signals, subrogation detection, agentic recovery workflow. Surfaced inside ClaimCenter — adjusters get guidance, not interruptions. Frontline's system: 38% faster cycle time.
Inline UW guidance with SHAP explainability. Straight-through processing where authority allows. Harborlight Mutual: 41% straight-through rate within 90 days, zero regulatory complaints.
Document extraction at FNOL, broker submissions, bordereau ingestion. Loss runs, photos, ACORDs, medical records, SOVs. Top-20 personal lines carrier: 4.2 days saved per claim on average.
RAG-grounded coverage Q&A inside producer and insured portals. Cites the policy form, not a model summary. FL Homeowner Mutual: 78% agency adoption within 6 months.
Quote, endorse, view-claim self-service on Guidewire Digital or modern web stack. AI-assisted where it accelerates the work; out of the way when it doesn't.
LLM extraction for treaty bordereau, capacity reporting automation, anomaly detection. Southcoast Re: 82% reduction in manual bordereau processing.
North-star definition, AI portfolio prioritization, ROI modeling, build-vs-buy decisions, regulatory roadmap. We start with the business case — not the technology.
The data foundation, MLOps platform, integration patterns. Snowflake or Databricks; SageMaker, Vertex, or Azure ML; the carrier's choice — but always production-grade.
UX patterns that build trust, not friction. Inline explainability for underwriters and adjusters. Change-management for the people who'll actually use the system every day.
The NAIC AI Model Bulletin, state DOI inquiries, internal audit — none of them tolerate "the model said so." Every production model we deploy ships with these six controls.
| CONTROL | WHAT IT DOES | WHY IT MATTERS |
|---|---|---|
| Drift Monitoring | Population & concept drift alerts on input features and predictions. | Catches model degradation before it shows up in loss ratios. |
| Bias Evaluation | Disparate-impact testing across protected and proxy classes, pre- and post-deployment. | NAIC Bulletin §4.2 readiness; state DOI fairness inquiries. |
| Explainability | SHAP / LIME on every individual decision, surfaced in adjuster & UW screens. | Defensible adverse action notices and reason codes. |
| Audit Logs | Immutable record of every input, output, model version, and downstream action. | Examiner-ready audit trail; reproducible disputes. |
| Model Cards | Versioned documentation: training data, metrics, intended use, known limitations. | Internal governance committees; vendor due diligence. |
| Rollback | One-click reversion to prior model version, with traffic shadowing during rollouts. | Safe deployment; no model becomes a hostage. |
We shipped Frontline's intelligent claims triage system alongside their PolicyCenter and ClaimCenter go-live — not as a future project. Same team. Same release cycle. Same milestone discipline.
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