AI-powered migration from Angular to React using microfrontends

Challenge

The entire legacy system was built with Angular 12. As part of their new strategy, the client decided to transition to React for all future front-end development. The main challenge was enabling a phased migration where Angular and React components could co-exist and evolve together without downtime or major rewrites of the codebase.

Our Approach: Why GenAI for Angular to React Migration

Given the initial requirements and a relatively limited timeframe, we proposed using a GenAI model to accelerate the conversion process.

By automating the initial translation from Angular to React, developers could focus on reviewing and refining the output rather than rewriting everything manually. This significantly reduced the time required to understand, rework, and test the code.

The approach resulted in a faster and more reliable migration.

Step 1 – Set Up the Microfrontend Architecture

We began by implementing a microfrontend architecture using the Single-SPA framework, allowing Angular and React modules to run side by side in the same application environment. This setup enabled teams to migrate features gradually without disrupting the overall system.

Step 2 – Ensure Incremental Feature Migration

With both frameworks coexisting, teams were able to migrate individual features or modules from Angular to React at their own pace. This minimized risk and avoided the need for a large-scale rewrite or downtime.

Step 3 – Introduced CodePilot for Migration Acceleration

To speed up the migration process, we built and deployed an internal tool called CodePilot, powered by GPT-4 via the OpenAI API. CodePilot provided AI-generated migration suggestions from Angular to React, helping developers work faster and more efficiently.

Generative AI was especially useful for navigating syntax differences, translating component logic, and handling repetitive migration patterns. These saved valuable developers’ time and reduced the risk of manual errors.

Step 4 – Secure and Compliant AI Integration

CodePilot was fully integrated into the client’s Azure environment. All AI interactions stayed on-premises, ensuring that no application code was sent outside the organization’s trusted infrastructure. This preserved intellectual property and met industry data security standards.

Results and Achievements

The hybrid architecture (microfrontends) enables continuous delivery, minimizes development risks, and offers a structured path toward full modernization. The integration of GPT-4-powered tooling has enhanced developer productivity, reinforced architectural consistency, and significantly accelerated the migration process.