One of the major challenges was integrating an AI-driven chat experience that could automatically categorize user queries into relevant ticket fields. Traditional ticketing systems rely on manual entry, which often leads to misclassification, slower response times, and inefficiencies. Our goal was to develop an AI-based system that could analyze user descriptions and accurately assign categories, reducing human effort and improving accuracy. Additionally, we needed to implement sentiment analysis to assess user feedback on products. The challenge was to extract meaningful insights from customer reviews and display them in an intuitive dashboard, allowing companies to track customer satisfaction and potential product concerns. Another significant challenge was providing business intelligence insights within the same system. We aimed to track product sales trends, usage growth over the last six months, and customer adoption metrics. The challenge was to present these insights in a visually digestible format, enabling businesses to make informed decisions on whether to churn, improve, or further invest in specific products.