My role at SparkAmplify merged project management with hands-on software engineering. I led a team of engineers, focusing on building chatbot applications that harness natural language processing and generative models. Our tools, including Prompt Engineering, LangChain, Vector Databases, Chainlit, and OpenAI APIs, were not just technical requirements but gateways to creating a chatbot that could communicate in multiple languages and process a range of document formats, from PDFs to URLs. This project was a testament to teamwork and the power of technology in solving real-world problems.
The central focus of our project was "Claire," a sales assistant chatbot designed for a ribbon company. Claire was engineered to navigate customers through a catalog of over 2000 ribbon products. Her functionality extended beyond just product recommendations. She could converse in multiple languages, making her a valuable asset to a global customer base. Here are the highlights of our enterprise solutions:
In the following video, I delve into the detailed workings of Claire, sharing the challenges and triumphs of this project. Join me in exploring the intricacies of AI in customer service 🥳 If your time is limited, you can skip to the product presentation at 2:10.
Looking back on this journey, I’m grateful for this opportunity to learn and apply various skills and tools in chatbot development. I want to thank my mentor, Chien Lee, for his guidance, support, and feedback throughout my internship. I would also like to thank Talent Circulation Alliance and Henry Lin for providing this opportunity to learn from business practitioners. I feel like I’ve found an interest and am growing very fast. I also look forward to continuing to explore the possibilities of applied generative AI and how it can improve our lives. Looking forward to the next journey of combining full-stack development and application of AI!