Modernized eight .NET libraries, APIs, and Functions in just two weeks using AI-powered automation—cutting delivery time by ~70% with zero downtime and no change to business behavior.
The client needed to modernize eight critical .NET components: libraries, APIs, and serverless Functions without disrupting live business operations. The landscape mixed legacy and modern .NET versions, custom database logic, and scattered configuration stored in multiple places.
Their goals were clear and high-stakes:
Internally, the client estimated 1–1.5 months of development effort and significant risk to ongoing operations. They needed a partner who could compress this timeline dramatically while reducing, not increasing, migration risk.
We combined deep .NET modernization expertise with AI coding agents and MCP-driven coordination to turn a multi-week migration into a two-week delivery.
Strategic migration design for seamless modernization
Incremental, verifiable implementation approach
Leveraging AI tools for rapid, accurate delivery
In just two weeks, we delivered a fully modernized .NET landscape with a consistent, future-ready architecture. All eight components were upgraded to supported .NET versions, wired into a centralized configuration service, and backed by automated migration and regression testing.
The client gained a platform that can be evolved and configured dynamically without risky redeployments or long maintenance windows while retaining the exact business behavior they trust.
The solution includes:
This case shows how complex .NET modernization doesn’t have to mean long freezes, risky cutovers, or massive teams. By combining AI-Powered Development, Code-to-Release Automation, and Cloud & DevOps best practices, we cut the expected modernization time by roughly 70% while actually reducing operational risk.
For the client, that means faster upgrades, a cleaner architecture, and full confidence that business processes continue to run exactly as before. For future projects, the reusable patterns, AI-enhanced workflows, and MCP-based knowledge layer now form a playbook they can apply again and again.
This is a concrete example of how Excality helps companies build smarter and adopt AI in real engineering workflows — turning modernization from a dreaded big-bang project into a fast, repeatable, and intelligent delivery process.
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