Empowering Developers with an AI-Powered Code Assistant for Proprietary Languages

A global enterprise software company with decades of experience in developing business management and analytics platforms. Their developer ecosystem works extensively with a proprietary 4GL programming language, which is central to their platform’s customization and extensibility.

The Need:
The client needed an internal chatbot capable of understanding, interpreting, and generating code in their proprietary 4GL language. The solution was expected to enhance developer productivity, reduce onboarding effort, and eliminate manual referencing—while ensuring cost efficiency and scalability.

Our Solution:
We developed a Retrieval-Augmented Generation (RAG)-based chatbot using an open-source LLM architecture, fine-tuned on the client’s 4GL codebase. The system was designed to retrieve the most contextually relevant code snippets, offer intelligent suggestions, and continuously improve via real-time user feedback. A lightweight backend ensured scalability and ease of deployment across dev teams.

Outcome Achieved:

• Successfully implemented a domain-specific AI assistant trained on proprietary code
• Enabled contextual code generation and explanation through embedded retrieval models
• Introduced real-time feedback loops for continuous learning and enhancement
• Improved developer productivity and onboarding experience across internal teams
• Deployed an enterprise-scalable, open-source infrastructure with minimal overhead