Put AI to work on insurance’s
hardest problems.
AI can help insurers underwrite faster, process claims more efficiently, detect fraud, and deliver better policyholder experiences. Openlayer helps teams test it, monitor it, and keep it under control in production.
See it in action
7 passing
1 failing
76%
of surveyed U.S. insurers have already implemented generative AI in one or more business functions.
Source: Deloitte, Scaling Gen AI in Insurance
74%
of insurers are investing in predictive analytics for underwriting and claims.
Source: EY, GenAI in Insurance Survey
25
jurisdictions have adopted the NAIC Model Bulletin on the Use of Artificial Intelligence Systems by Insurers.
Source: NAIC, April 2026 implementation map
Insurers need to move faster without losing control.
AI is moving into some of insurance’s highest-impact workflows. The opportunity is enormous, but so is the cost of getting a decision wrong.
Underwriting still depends on too much manual review.
Underwriters spend valuable time gathering information, reviewing documents, reconciling data, and evaluating routine risks. AI can accelerate the work, but decisions around eligibility, pricing, and coverage need to remain accurate, explainable, and fair.
Claims teams are under pressure to make faster, better decisions.
Claims require teams to interpret documents, policy language, images, histories, and customer communications at scale. Automation can dramatically reduce handling time, but errors can directly affect policyholders and loss costs.
Every AI-assisted decision has to stand up to scrutiny.
Insurers need to know which AI systems are being used, what data they rely on, how they perform across different populations, and whether they continue to behave as intended. Regulators increasingly expect those controls to be documented and demonstrable.
AI can now take on the work slowing insurance down.
AI can review submissions, extract information from documents, interpret policy language, identify patterns, summarize complex files, detect suspicious activity, and support multi-step workflows across underwriting, claims, operations, and service.
That changes what insurers can automate. But when AI influences pricing, eligibility, claims, coverage, or customer communication, a successful pilot is not enough. Teams need to know how every system performs before release, what it is doing in production, and when its behavior changes.
Move insurance AI into production with control.
Openlayer connects pre-release testing, production monitoring, safeguards, governance, and evidence. AI teams can improve systems faster while risk, compliance, and business teams can see what changed, how it performed, and which controls were applied.
Faster, more consistent underwriting.
Test risk classifications, recommendations, explanations, and decision quality before release. Monitor models, data, thresholds, and outcomes as conditions change.
Claims automation you can trust.
Evaluate claims triage, document extraction, coverage analysis, summarization, and recommendations against known outcomes and business rules. Catch failures before they affect policyholders.
Smarter fraud detection.
Measure false positives and false negatives, trace why systems flagged a claim or transaction, and use production outcomes to continuously improve detection.
Policyholder service that stays accurate.
Test customer-facing assistants for factual accuracy, policy interpretation, required disclosures, escalation behavior, and sensitive-data handling across complete conversations.
Safer agent and employee copilots.
Make sure copilots retrieve from approved sources, follow internal policies, handle customer data appropriately, and give agents and employees answers they can rely on.
Consistent third-party AI oversight.
Apply the same testing, monitoring, and governance standards to external models and AI vendors. Track model versions, changes, incidents, performance, and evidence in one place.
Built for AI that operates in regulated environments.
Trusted by insurance leaders including Sun Life and Gallagher.
SOC 2 Type II.
Founded by ex-Apple/Siri ML engineers.
Air-gapped and private-VPC deployment options for sensitive insurance data.
Named in the 2026 Gartner Market Guide for AI Evaluation and Observability Platforms.
Openlayer gives insurers one place to inventory AI systems, test them before deployment, monitor them in production, enforce controls, and retain evidence of how they performed. Teams can connect technical performance with ownership, risk, approvals, policies, and regulatory requirements.
Openlayer helps insurers operationalize many of the governance practices expected under the NAIC Model Bulletin, including AI system inventories, documented ownership, testing, ongoing monitoring, risk controls, third-party oversight, and evidence that can be reviewed during an examination.
Yes. Insurers can evaluate underwriting models and AI applications for decision quality, accuracy, consistency, explainability, and performance across relevant groups before deployment and continuously after release.
Yes. Openlayer lets teams define and continuously run tests for performance differences across customer groups, monitor changes over time, and retain the results alongside model documentation and governance evidence.
Teams can test and monitor AI used for claims triage, document extraction, summarization, coverage analysis, fraud detection, and decision support. Openlayer helps verify that outputs remain accurate and aligned with policies as models, prompts, data, and workflows change.
Yes. Openlayer evaluates complete AI systems, not just traditional predictive models. Teams can test LLM applications and agents for accuracy, tool use, policy adherence, data handling, hallucinations, and task completion, then monitor the same behaviors in production.
Insurers can register third-party models and applications alongside internally developed systems, apply consistent evaluation standards, monitor changes and performance, and maintain a history of versions, tests, approvals, and evidence.
No. Openlayer integrates with existing risk, compliance, model development, and data infrastructure. It adds the testing, monitoring, runtime controls, and AI-specific evidence needed to understand how systems actually behave.
Yes. Openlayer is designed for large organizations deploying AI across multiple teams and business units, with support for private environments and air-gapped deployments where sensitive data cannot leave an insurer’s infrastructure.
AI is moving beyond experimentation and into underwriting, claims, fraud, customer service, and other workflows that directly affect policyholders. At the same time, regulators are increasing their focus on AI governance, fairness, explainability, third-party models, and evidence that controls are actually working.
Build better insurance systems with AI.
Move from AI pilots to production with the testing, monitoring, and controls to know your systems are working as intended.