AI Insurance Research Lab

Open benchmarks, playbooks, and quarterly insights to accelerate safe, effective agent adoption.

Where insurance-domain rigor meets agentic AI engineering. Reproducible benchmarks, governance playbooks, and a readiness index—so you can adopt faster, safer, and audit-ready.
Open Benchmarks
Intake, coverage, explainability, fairness.
Playbooks
Adverse action, rationale templates, HITL.
Readiness Index

Assess org readiness across dimensions.

7.8 / 10
Quarterly Insights
Trends, architectures, anonymized learnings.
Open Benchmarks (Insurance-Native)

Each benchmark ships with datasets/specs, metrics, scoring logic, and governance notes. 

Document Intake & Normalization

Tasks
Metrics

Coverage & Exception Analysis

Tasks
Metrics

Quote Comparison & Explainability

Tasks
Metrics

Underwriting Signals & Referral Reasoning

Tasks
Metrics

Claims FNOL & Triage

Tasks
Metrics

Fairness & Robustness Checks

Tasks
Metrics

Suitability & Adverse Action

Tasks
Metrics

Policy Service Automation

Tasks
Metrics

Treaty & Bordereaux QA

Tasks
Metrics

Cat/Event Analytics

Tasks
Metrics
Readiness Index (Assessment)

Measure your posture and get a gap-aligned plan.

7.8
Overall / 10

Governance
69%
Data & Tools
74%
People & Skills
65%
Change & Adoption
71%
Playbooks (Governance-First)
Production-grade templates you can adopt as-is or tailor.
Governance & Risk
Explainability & Language
Operations & HITL
Data & Privacy
Quarterly Insights
Trends, reference architectures, and anonymized field learnings.

Where STP Works, Where Agentic AI Excels, and Where HITL Must Stay

Decision Segmentation and Cost Curves for Document-Heavy Workflows in the Age of Agentic AI

Reference Architectures for Governed RAG/Agents

Patterns for claims triage and UW explainability packs in regulated stacks.

Benchmark Trends: Accuracy vs. Latency

How carriers balance P95 latency with explainability and reviewer throughput.

Methodology & Assurance
Participate

Is this model ranking?

It’s use‑case benchmarking with governance signals, not just raw model scores.

Can we run it internally?

Yes—on‑prem private harness with the same metrics and artifact factory.

What about sensitive documents?

Use redaction + synthetic recipes; we provide contracts and SOPs for PHI/PII.

Ready to test, learn, and scale—safely?

Kick off with benchmarks, tailor playbooks, and get your readiness plan in days—not months.