How Gen AI Accelerated a Phased ColdFusion to .NET Modernization for a Multinational Semiconductor Manufacturer

About the client:

Our client is a multinational semiconductor manufacturing company with a strong focus on innovation and efficiency. To stay ahead in the industry, they initiated a company-wide technology standardization effort, migrating all legacy applications to .NET. 

However, this journey required an interim step, first transitioning ColdFusion applications to PHP before moving to .NET. The complexity of this multi-stage modernization, combined with a lack of documentation, security concerns, and AI governance restrictions, made the project particularly challenging.

Challenge

The client, a multinational semiconductor manufacturing company, sought to modernize its legacy applications while adhering to a strict .NET-first strategy. As an interim step, they were migrating ColdFusion applications to PHP before the final transition to .NET. They needed a framework that aligned with this phased approach without introducing conflicting architectures.

A major roadblock was the lack of documentation—many applications had no records of business logic, workflows, APIs, or dependencies, and the original developers were unavailable. Additionally, their reliance on SonarQube for code analysis proved insufficient, as it failed to detect deeply embedded issues and cognitive complexity.

Testing was another challenge, with no existing automated test cases to validate functionality post-modernization. They required a way to generate test cases, user stories, and acceptance criteria.

Strict AI governance policies limited the use of certain LLMs (Amazon Titan, BigScience, Llama, GPT-4) for internal applications. They needed assurance that no sensitive data would leave their firewall while exploring integration with their proprietary AI models.

On the infrastructure front, deployment flexibility was a concern—they needed clarity on running the platform across AWS, on-premise, or multi-cloud environments. Cost and ROI justification were also critical, as they required a clear comparison between manual and automated modernization to gain internal buy-in.

Lastly, internal approvals posed a hurdle, with decision-making dependent on U.S.-based stakeholders and compliance reviews from their AI governance team.

Solution Architecture:

Legacyleap provided a structured modernization framework that aligned with the client’s phased ColdFusion → PHP → .NET modernization strategy.

Strategic Alignment with Modernization Plan:

• Ensured each phase aligned with the company’s .NET-first strategy, avoiding architectural misalignment.
• Provided a fitment score to evaluate different modernization approaches while reinforcing the final .NET transition.

Automated Documentation & Code Analysis:

• Extracted business logic, workflows, APIs, and dependencies to generate structured documentation.

• Created interactive flowcharts and mind maps for better developer understanding.

• Enhanced SonarQube with AI-powered analysis to detect deep-seated bugs and cognitive complexity.

Test Case Generation & Functional Validation:

• Automatically generated unit tests, integration tests, API test suites, and UI test cases.

• Developed user stories with personas and acceptance criteria to ensure functional parity post-modernization.

AI Governance & Security Compliance:

• Supported on-premise and private cloud deployments, ensuring sensitive data never left enterprise firewalls.

• Deployed an AI middleware layer to isolate LLM interactions, preventing unauthorized exposure.
• Integrated self-hosted AI models like AWS Bedrock to comply with internal governance policies.

Seamless AI & Infrastructure Integration:

• Provided a configurable AI middleware layer for seamless integration with the client’s internal LLMs.
• Ensured AI prompt optimization for maximum efficiency within the enterprise environment.
• Offered flexible deployment options across AWS, GCP, on-premise, or hybrid environments with Kubernetes support.

Cost Justification & ROI Analysis:

• Delivered a comparative ROI analysis demonstrating 40-50% cost savings through automated modernization.
• Provided financial estimates to aid internal budget approvals and decision-making.

Results: