Challenges Slowing AI Transformation In Insurance
Regulatory Compliance
Strict data privacy laws like GLBA and NAIC model governance require full traceability, strong data controls, and usage audits
Complex Legacy Systems
Claims management, underwriting, CRM, and billing systems (e.g. Duck Creek Policy / Claims) often operate in silos
Secure Data Boundaries
Sensitive policyholder data must remain inside controlled environments, requiring on-prem or in-region deployments
Enterprise AI architecture for regulated insurance data
AI Gateway for centralized, compliant model access
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- Standardize risk scoring and claims automation by routing all models (OpenAI, Claude, internal LLMs) through a single AI Gateway / LLM Gateway with governed access and token-level audit logs
- Apply GLBA- and NAIC-aligned controls using RBAC, customer metadata tagging, and usage policies to ensure compliant underwriting and fraud evaluations
MCP Gateway for governed agent actions in core systems
- Enable AI agents to interact securely with tools like Guidewire, Duck Creek, Salesforce, etc. through one MCP Gateway, without exposing system credentials
- Govern every agent action through MCP Registry rules that enforce role-based permissions and system boundaries
Deploy AI in insurer-controlled environments
- Run LLMs and agent workflows inside on-prem AI platforms, air-gapped networks, or VPCs to comply with GLBA, NAIC Data Security Model Law, and state data-residency laws
- Keep policyholder PII, PHI, and other confidential data within your existing security perimeter, ensuring no external model provider exposure
Scale operational efficiency in insurance with agentic AI built on TrueFoundry
Premium billing agent
Claims processing agent
Fraud detection agent
Underwriting copilot
Policy recommendation agent
Renewals agent
The computing costs savings we achieved as a result of adopting TrueFoundry, were greater than the cost of the service (and that's without counting the time and headaches it saves us!)
GenAI infra- simple, faster, cheaper
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