Enterprise-ready library of 50+ AI agents purpose-built for insurance industry complexities
NEW YORK and SINGAPORE, a leader in AI-powered intelligent automation for insurers, today announced the release of its AI Agent Library, designed to help insurers operationalize artificial intelligence across claims, underwriting, servicing, and distribution.
Neutrinos supports insurers through the entire implementation journey, helping discover opportunities for agent adoption, design multi-agent workflows, build and integrate agents, and scale AI deployments with governance and observability. Delivered through the Neutrinos intelligent automation platform, the library enables agentic AI orchestration at scale.
“For insurers looking to get started with agentic AI, this library delivers a fast, scalable, frictionless on-ramp,” said Samik Ghosh, CEO and Co-Founder of Neutrinos. “Whether these are your first AI agents or you’ve already built some in-house or with other partners, the Neutrinos platform works alongside them. This library of agents reflects real-world insurance use cases and gives teams a practical, enterprise-grade foundation to deploy context-aware, governed AI without starting from scratch.”
Neutrinos AI Agent Library includes purpose-built models for insurance value streams across:
- Claims Automation: Deploy AI agents to orchestrate intake, verify claims data, and support adjudicators with context-aware decisions.
- Underwriting & Risk Assessment: Model risk, analyze documents, and recommend next best actions.
- Fraud Detection & Adjudication Support: Detect anomalies, validate evidence, and flag risk signals in real time.
- Customer Communication & Engagement: Support context-aware interactions across the policyholder lifecycle.
- Medical & Document Intelligence: Classify, extract, and analyze unstructured data across both underwriting and claims processes.
- Distribution Support & Compliance: Support case collaboration, agent oversight, and audit-readiness.
“Insurers can introduce AI agents at any point in the business process, automating manual tasks or accelerating time to value, with seamless handshakes to legacy or modern platforms, minimizing disruption to existing systems,” added Ghosh.
