Key Insights: We built an agentic disability claims processing platform for a Fortune 100 insurance enterprise, helping structure complex adjudication logic, compress technical alignment from weeks into a couple of days, and create a production foundation for over 500,000 claims processed annually.

About the Client

We’ve had the opportunity to work closely with one of the world’s largest insurance enterprises on a high-complexity AI initiative: bringing automation into their disability and leave-related claims operations.

The client processes over 500K claims a year in a highly regulated environment where every decision depends on federal, state, and employer-specific rules. These are not simple transactions; they require documentation, eligibility checks, benefit calculations, exceptions, and human review, all of which need to remain traceable and compliant.

The Challenge

The goal was to automate one of the client’s most complex operational workflows: disability claims adjudication, starting with maternity as the initial implementation.

• Complex Multi-System Workflows: Maternity cases often combine Short-Term Disability and Absence components, each requiring independent entitlement checks, benefit calculations, offsets, and decision criteria.
• Fragmented Knowledge Base: Rules were scattered across plan documents, statutory regulations, internal software, employer guides, and the institutional memory of individual claims operators.
• Scaling Bottlenecks: Onboarding a new employer plan meant manually rediscovering and validating rules from scratch, making the process slow to scale, hard to audit, and prone to inconsistency.

The client needed to reduce manual effort and drive consistency without compromising human oversight, compliance, or auditability.

Marvik’s Approach & AI Forward-Deployed Engineers Execution

Before writing a line of code, we ran an on-site alignment session with the client’s IT and compliance teams. This helped resolve technical, operational, and compliance decisions early, accelerating kickoff by more than two weeks.

From there, our team worked directly with claims specialists to understand how decisions were actually made. We helped surface undocumented rules, define ownership across workstreams, and turn fragmented claims knowledge into a structured, buildable system.

The solution was designed as an agentic platform covering the disability claims lifecycle:

• Knowledge Base: We structured employer-specific rules, eligibility conditions, benefit formulas, offsets, and source relationships into a queryable and auditable knowledge layer.
• Claim Processing Agents: We built specialized absence and short-term disability agents to apply rules, perform calculations, flag missing information and contradictions across documents, and prepare source-backed recommendations for human approval.
• Evaluation Framework: We defined golden datasets and accuracy thresholds to validate agent performance before broader production rollout.
• Live Operations Interface: We designed an interface where associates can review claim-level AI reasoning, managers can monitor performance, and leadership can access operational metrics.
• Reusable Agent Harnesses: We created shared foundations to standardize how future claim workflows are built, tested, governed, and deployed.

The Results & Impact

• Technical alignment accelerated: The on-site kickoff compressed weeks of alignment into 2 focused days and helped move the project forward faster.
• 500K+ claims supported annually: The platform foundation is designed to support one of the client’s highest-volume claims lines.
• Claims logic made structured and auditable: Rules, calculations, sources, agent reasoning, and human actions are organized into a traceable workflow.
• Human oversight preserved: Associates remain in control of critical decisions, with AI supporting review, recommendation, and documentation.
• Reusable foundation for scale: The same knowledge structures, evaluation patterns, and agent harnesses can support future claim types and employer plans.

Why This Matters

Enterprise AI doesn't reach production through software alone. It demands deep domain context, cross-functional alignment, clear governance, and an engineering model that bridges high-level business goals with production delivery.

This project reflects how Marvik operates: AI-native since 2018 and forward-deployed by design. We work inside your actual environment, aligning IT, compliance, and business units to turn undocumented operations into scalable, governed, and production-ready AI platforms.