This talk will start by answering the question: What is conversational analytics and how does it work? After which we'll dive into why this was built and how the implementation was done.

• How analytics in SaaS can be fundamentally improved by conversational analytics (5 mins).
• How the Text-to-SQL fundament was shaped using RAG with Embeddings in PGVector (5 mins).
• Dealing with multi-tenancy in PostgreSQL and BigQuery to ensure data segregation & security (5 mins).
• How to handle tenant specific pre-training and training examples (5 mins).
• Building this into an existing application and supporting integrations (5 minutes).
• Conclusion and thoughts on the implications for the field of analytics (5 mins).

In the end you should have a good idea on why conversational analytics can be a game changer, what the pitfalls are and how to build it with open source technologies.