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Case Study

Legacy platform modernization for a mid-market compliance software provider

A decade-old SOAP/WCF platform moved to REST APIs without taking live enterprise customers offline.

The problem

A mid-market compliance and risk-management software provider ran a decade-old platform for supplier-diversity and regulatory spend reporting, used by enterprise and industrial customers across manufacturing, energy, and regulated sectors. Its services layer was still SOAP/WCF, tightly coupled to business logic and database interactions accumulated over years of development.

The work ran under four constraints:

• Dependencies no one had mapped. Years of development had produced references and integration points that had to be traced before any service could be replaced.
• Business logic that had to survive intact. Migrated endpoints needed to behave the same as the SOAP services they replaced.
• No acceptable downtime. Enterprise customers ran workflows on the platform throughout.
• Thin regression coverage on a mature, interconnected codebase, which made refactoring riskiest in the places that needed it most.

What our team built

Two parallel workstreams. In both, AI worked as an engineering partner under developer review rather than as a code generator.

API modernization. Legacy SOAP/WCF services re-engineered to REST on a modern runtime, with AI handling class-to-functional translation, file decomposition, cross-file pattern consistency, and type verification. A phased approach kept SOAP and REST serving simultaneously, so downstream consumers migrated on their own schedule rather than on a cutover date.

UI/UX modernization. AI read the existing codebase to map implementation patterns, dependencies and impacted components before anyone changed them, then executed the repetitive multi-file edits that follow. AI-assisted implementation covered 60–80% of the work. Developers reviewed and validated every generated change.

The outcome

• ~50% reduction in development effort on the API migration, with engineering review retained throughout.
• ~50% reduction in code-analysis effort: understanding legacy business logic, references and integration points before touching them.
• ~50% reduction in R&D time from requirement analysis to implementation.
• A 19-file coordinated change completed in roughly 5–10 minutes, against the hours the same refactor used to take.
• Delivery throughput from ~10 to ~67 user stories per month, a 6.7× observed increase on the modernization roadmap.
• No disruption to live customers during the phased transition.

The boundary of this claim

These are brownfield gains in analysis, refactoring and migration throughput. We make no claim that AI helped engineers invent features faster. Published research puts AI coding gains far lower on legacy code than on greenfield work, so the gain here came from making an opaque codebase legible first. The velocity figure reflects observed delivery throughput on this roadmap, not a general benchmark.

Sizing basis: providers in this software category typically run 500–1,000 employees and serve enterprise clients with 500 to 50,000+ employees each in heavily regulated industries.

Tools & technology

• Claude
• GitHub Copilot
• Cursor
• .NET Core
• REST APIs
• SOAP / WCF (legacy)
• TypeScript

Not ready to book yet? Read another case study — insurance-document automation or test-automation acceleration.