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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.

Key Results

  • ~70% faster delivery than planned
  • Full modernization completed in 2 weeks
  • Zero downtime with dynamic configuration
  • Business logic behavior verified unchanged

Technologies Used

.NET Core 3.1 .NET 6 .NET 8 Azure Functions Azure App Configuration SQL Server Claude Code Microsoft Copilot OpenAI Codex Context 7 MCP Atlassian MCP
.NET Modernization - 70% Faster Delivery Illustration

Challenge

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:

  • Upgrade frameworks - Move from legacy .NET Core 3.1 to modern .NET 6 and .NET 8
  • Database migrations - Perform tailored migrations with custom logic
  • Centralized configuration - Move all configuration into a dynamic service for instant updates without redeployments
  • Zero behavior change - Every existing business rule had to behave exactly as before

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.

Our Approach

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.

Architecture & Planning

Strategic migration design for seamless modernization

  • Created a unified migration plan for all libraries, APIs, and Functions
  • Standardized upgrade paths for .NET Core 3.1, 6, and 8
  • Designed centralized configuration to enable instant updates without redeployments

Development & Delivery

Incremental, verifiable implementation approach

  • Upgraded codebases in small, verifiable steps
  • Refactored configs, dependencies, and runtime logic to fit the new architecture
  • Strengthened automated tests to confirm that all business rules behaved identically post-migration

AI-Driven Acceleration

Leveraging AI tools for rapid, accurate delivery

  • Used Claude Code, Copilot, and Codex to automate repetitive refactoring and validate database migrations
  • MCP tools ensured precise coordination and consistent documentation across the entire migration
  • Speed up multi-repo updates with AI-enhanced workflows

Solution

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:

  • Unified configuration service for all libraries, APIs, and Functions
  • Automated database migration playbooks aligned with application changes
  • Regression test harness for critical business workflows
  • Enhanced observability and health checks to support zero-downtime releases
  • Standardized modernization patterns reusable for future components

Why It Matters

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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