CSX Bot is an intelligent customer support virtual assistant designed to streamline technical issue resolution through a modern conversational interface. The system leverages Retrieval Augmented Generation (RAG) technology to provide contextually relevant support by accessing company documentation and seamlessly integrates with ticket management systems.
As one of the two AI engineers on the project, I contributed to developing a comprehensive solution that bridges the gap between automated support and human intervention, making technical assistance more accessible and efficient for users experiencing issues with company products or services.
Ensuring the AI could properly understand complex technical inquiries while maintaining conversation context was a significant challenge.
Solution: I implemented a sophisticated RAG architecture using LangChain and ChromaDB that retrieves relevant documentation snippets to augment the AI's responses, resulting in more accurate and helpful technical guidance.
Creating a system that could identify when human intervention was needed without frustrating users required careful design.
Solution: I developed the ticket creation and agent routing functionality that seamlessly transitions from automated support to human assistance when necessary, capturing all relevant conversation context for efficient issue resolution.
Integrating diverse technical documentation into a queryable knowledge base presented technical challenges.
Solution: I implemented the vector store system that efficiently processes and indexes company documentation, enabling semantic search capabilities that produce relevant information based on user queries.
The CSX Bot system has become an essential support tool, demonstrating significant impact:
Working on the CSX Bot enhanced my expertise in developing practical enterprise AI solutions and provided valuable insights into creating effective support automation systems. I gained deep experience in: