Governance Advisory
Design governance strategies, approval workflows, and operating models that help insurance teams move AI initiatives into compliant, production-ready use across business units.
Help underwriting, claims, and risk teams move from AI pilots to governed production systems with real-time controls, auditability, and policy enforcement. Trussed AI supports insurance organizations that need stronger oversight for LLMs, copilots, and agents without slowing operational workflows or creating manual review bottlenecks.
Governance, control, and assurance solutions for insurers deploying AI across underwriting, claims, and internal operations.
Design governance strategies, approval workflows, and operating models that help insurance teams move AI initiatives into compliant, production-ready use across business units.
Enforce runtime policies across AI apps, models, and agents with centralized controls, audit logging, security guardrails, and regulator-ready reporting.
Apply real-time boundaries to agent actions, tool calls, and workflow triggers so autonomous systems operate within approved insurance policies and controls.
Generate continuous audit evidence for AI interactions, including policy decisions, model versions, timestamps, and traceability for internal and external reviews.
Track AI spend by team, workflow, and provider while enforcing budgets and optimizing model selection for cost-effective insurance operations.
Map governance to regulatory and risk requirements with continuous monitoring, policy enforcement, and records that support oversight in regulated environments.
Trussed AI helps carriers and underwriters govern LLMs, copilots, and agentic workflows where decisions actually happen. Instead of relying on static policies or after-the-fact reviews, the platform applies controls in real time, maintains complete audit trails, and gives risk, compliance, and technology teams shared visibility into AI usage, behavior, and outcomes.
See how regulated organizations strengthen AI oversight, audit readiness, and operational control.
Built for enterprises that need AI governance to work in production, not just on paper.
Policies are enforced during live AI interactions, not after underwriting or claims workflows complete.
Every governed interaction creates traceable evidence for compliance, internal audit, and regulatory examination teams.
Supports regulated insurance environments where oversight, approvals, and defensible decision records are essential.
Founded by leaders from Google Cloud, AWS, Adobe, Microsoft, Cisco, and other enterprise platforms.
Experienced founders building governed enterprise AI infrastructure.
Co-Founder
Ajay Dankar is Co-Founder of Trussed AI and brings nearly three decades of cloud product and engineering leadership to enterprise AI governance. His background includes senior roles at Google Cloud, AWS, Adobe, and PayPal/eBay, where he worked on scaling, reliability, and cost optimization for complex production systems. At AWS, he led product management for Elastic Load Balancing, helping drive broad adoption and operational savings. He also founded Finsphere, later acquired by Visa, where he helped pioneer fraud detection using mobile location data. That blend of infrastructure depth, regulated-data awareness, and enterprise execution informs Trussed AI's approach to runtime governance, resilience, and auditability for organizations deploying generative and agentic AI at scale.
Co-Founder
Branden McIntyre is Co-Founder of Trussed AI and focuses on building infrastructure that helps enterprises deploy AI reliably at scale. Across product roles at Rakuten, Cisco, JustAnswer, and Oracle, he saw the same challenge repeatedly: organizations could experiment with AI, but lacked the tooling and controls needed for safe production deployment. His work leading AI prediction initiatives improved customer experience and platform efficiency while exposing the operational gaps between prototypes and governed systems. At Trussed AI, Branden applies that experience to help enterprises implement AI with stronger oversight, reliability, and execution-layer controls. His background combines practical machine learning deployment knowledge with enterprise product strategy, making him closely aligned with the needs of regulated teams adopting AI in high-stakes workflows.
Co-Founder
Sunita Reddy is Co-Founder of Trussed AI, where she leads AI, operations, and partner strategy for enterprise adoption of generative and agentic AI. With more than two decades of experience across product, AI, and design, she specializes in turning emerging technologies into scalable, enterprise-ready solutions. At JustAnswer, she led initiatives that integrated large language models into core workflows, including copilots, conversational interfaces, and human-in-the-loop systems that improved engagement and accuracy. Earlier roles at Microsoft and Accellion strengthened her expertise in product innovation, partnerships, and enterprise collaboration platforms. She also holds multiple patents in location-based fraud detection. At Trussed AI, Sunita helps shape governance approaches that balance innovation, operational practicality, and the oversight requirements of regulated industries such as insurance.
In insurance, an LLM is a large language model used to support tasks such as underwriting summaries, claims documentation, policy analysis, customer service, and internal knowledge retrieval. When deployed in production, LLMs need governance controls for data access, prompt handling, output review, audit logging, and policy enforcement so carriers can manage risk, compliance, and operational consistency.
Talk with our team about controls, audits, and deployment options.
Independent controls validation for security operations.
Recognized information security management standard.
Supports structured AI risk management practices.
Share your insurance AI use cases, governance goals, and deployment requirements. Our team will help you evaluate the right controls, architecture, and rollout approach.
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To help us assist you faster, please include the reason for your message so the relevant team can reach out as soon as possible.