Privacy-First Chatbot Enhancement in Finance with Databricks and Gretel

This blog post demonstrates a solution for enhancing customer support chatbots in the finance industry while maintaining privacy. The challenge lies in leveraging sensitive customer interaction data to improve support without compromising privacy. Synthetic data, generated using Gretel's Navigator Fine Tuning and stored in Databricks File System (DBFS), offers a powerful solution by creating purpose-built datasets that maintain the statistical properties of the original data without exposing sensitive information. This allows financial institutions to provide contextual information to their chatbots and leverage Retrieval Augmented Generation (RAG) workflows safely, effectively improving customer experience while maintaining strict privacy standards.