Internal Code Assistant
A custom AI assistant trained on a company's private codebase to help developers write better code, faster.
Project Overview
A large tech company with millions of lines of proprietary code needed a way to help new and existing developers navigate their complex internal libraries and coding standards.
The Challenge
Onboarding new developers was slow, and even experienced engineers spent hours searching for documentation or asking for help with internal APIs.
My Solution
I built a secure, on-premise code assistant, similar to GitHub Copilot but trained exclusively on the company’s private repositories.
Secure Data Indexing: I used a vector database to index the entire codebase without exposing it to external services.
Context-Aware LLM: The assistant was integrated into the developers’ IDEs, providing context-aware code completions, explanations, and documentation on the fly.
Enforcing Best Practices: The model was fine-tuned to suggest code that adhered to the company’s specific style guides and best practices.
The tool has reduced developer onboarding time by an estimated 40% and has become an indispensable part of the engineering workflow.