Reclaiming Control of a High-Cost Integration Platform

How a major insurance provider partnered with Nomura Research Institute (NRI) to replace a substantial legacy integration environment with an AI-accelerated modernization approach, reducing external dependency, expanding test coverage, and restoring internal ownership.

Business Situation

A commercial property and casualty insurer, relied on a third-party integration platform to power a mission-critical API ecosystem connecting agents, quoting systems, and core business services.

While operationally functional, the environment created growing financial and operational pressure:

-Substantial annual licensing and professional services costs

-Limited internal visibility into application behavior

-Ongoing reliance on external specialists for updates and support

For executive leadership, the issue centered on financial control and strengthening internal expertise. Recurring licensing costs continued to rise, and critical system knowledge remained external. Multiple modernization efforts had already stalled.

The client needed to reduce financial exposure while restoring internal ownership and protecting operational stability.

Facing cost pressure, architectural constraints, and aggressive timelines, the IT team identified several critical considerations:

Align IT and finance around shared objectives
Implement a modern, supportable architecture aligned with internal capabilities
Reduce long-term licensing and external services dependency
Complete modernization within months with full transparency, documentation, and testing, without multi-year funding risk
Regain internal ownership of integration services

The Approach

NRI introduced a differentiated modernization model: AI-Accelerated Application Development powered by its AI Adaptive Engine.

Rather than treating modernization as a conventional migration project, NRI embedded AI across the entire lifecycle: discovery, requirements analysis, code transformation, documentation, and testing.

The engagement began with a six-week proof of concept to validate whether AI could:

  • Rapidly analyze and understand the legacy integration environment
  • Generate documentation and requirements at enterprise scale
  • Compress delivery timelines without increasing operational risk

The results confirmed our multi-agent AI’s ability to function as a structural accelerator across the modernization effort, materially increasing speed, scale, and execution capacity.

Scaling Execution with AI at the Core 

Following validation, a joint team of experts executed full modernization over 7–8 months. 

The scope included: 

  • Migration of 38 integration applications 
  • Modernization of approximately 700 API endpoints, roughly half of which were highly complex 
  • Transition to a modern, internally supportable architecture 
  • Continuous business validation to ensure functional fidelity 

The AI Adaptive Engine accelerated: 

  • Deep system discovery and architectural analysis 
  • Automated requirements extraction 
  • Large-scale documentation generation 
  • Code refactoring and transformation 
  • Automated test creation 

AI-augmented engineering teams enabled the client to operate at materially higher velocity and scale throughout this modernization effort. The result: enterprise-scale modernization completed in under a year. 

The Outcome 

Working with NRI, the client successfully transformed a high-cost, externally dependent integration platform into a modern, internally owned foundation. 

The organization achieved: 

  • Reduced recurring licensing exposure 
  • Restored internal control and expertise 
  • Expanded documentation and governance 
  • Dramatically improved testing and resiliency 
  • A repeatable AI-driven modernization approach for future initiatives 

For finance leaders, the transformation delivered greater cost predictability and reduced vendor dependency. For IT leadership, it delivered architectural control, improved governance, and accelerated modernization capacity. 

This engagement reflects NRI’s broader Data & AI philosophy: applying advanced, multi-agent AI capabilities as embedded accelerators within core enterprise transformation initiatives. 

Capabilities Applied

AI Accelerated Application Development
API Migration & Refactoring
AI Adaptive Engine Tooling
Legacy Application Modernization

Technologies Referenced

MuleSoft (Legacy Integration Platform)
NET Application Stack