AI-assisted .NET app modernization: From Windows Forms to a web architecture
How can you accelerate the preparation of a locally installed .NET application for migration to an intranet web system without losing business logic, access rules, or the familiar interface structure? WaveAccess used AI to extract rules from the source code, validate them with the client, and build a web proof of concept. In the pilot, the requirements handoff to development was reduced from several weeks to several hours.
Client profile
A large engineering and manufacturing company relied on the application to give several hundred engineers controlled access to technical content and specialist tools used in daily work.
Why the legacy .NET application became an operational risk
The .NET and Windows Forms catalog ran locally and provided a tree of projects, technologies, and topics with related content and project-based access controls.
The application combined reference content, content storage, and access to engineering software, but only the specialist who built and maintained it fully understood its structure and logic as he approached retirement.
Local deployment also limited use across devices, so the client needed to prepare a move to an intranet web application while preserving the catalog structure, access controls, and core workflows.
Why not every Windows Forms feature should move to the web
Automatic software installation was part of the original desktop workflow, but reproducing it directly in a browser would have introduced technical and security risks.
WaveAccess and the client identified which capabilities still mattered and replaced automatic installation with controlled links to approved installers, preserving access to required tools without carrying unsafe desktop behavior into the web architecture.
How WaveAccess extracted business logic from the .NET codebase
Much of the business logic and user-interface structure was available as text in the .NET codebase. WaveAccess created specialized AI agents and prompts to analyze the code, identify access rules, map relationships between catalog sections, and describe interface behavior.
The analysis produced structured business rules and requirements that the client reviewed and confirmed as an accurate description of the existing system.
After validation, the team created a web proof of concept with a familiar tree and content view to demonstrate the move to a modern stack without redesigning the interface.
The solution architect and product owner reviewed every AI-generated artifact, kept it aligned with the business need, and decided which legacy behaviors should move to the new architecture.
Business outcome
The pilot converted knowledge held by one developer into structured business rules validated by the client, reducing dependence on a single specialist before his retirement.
In the pilot, preparing the requirements and handing a usable task to development took hours instead of several weeks of repeated handoffs between the client, analyst, and developer.
The team also demonstrated that the familiar catalog structure and access logic could be recreated in a web architecture while removing browser-inappropriate functions.
The pilot showed that AI shortens the path from source code to validated requirements while architects and product owners remain accountable for the final system.
How AI supports .NET application modernization
In .NET modernization projects, AI is particularly valuable during code analysis and preparation for the target system. It can identify business rules, connect functions with data and interfaces, prepare requirements, and generate early artifacts for the new architecture.
AI does not own the final product. WaveAccess uses validation gates: the client confirms business logic, engineers control architecture and quality, and generated components and tests go through technical review. The process reduces routine work and allows senior experts to focus on high-value decisions.
