The session elucidates the methodology to develop conversational agents by using an internal knowledge base, with a primary focus on the following key facets:
- Designing the solution to align with the foundational principles of AI engineering, concurrently harnessing the conversational proficiencies of the Language Model (LLM).
- Crafting the solution within the framework of a serverless cloud infrastructure.
- Systematically engineering the solution to ensure scalability within a production environment.

In particular, the session is meant to provide the perspective of BIP xTech on creating AI-based assets such that they are sustainable and effective in production with a massive amount of users.

Furthermore, we demonstrate how to integrate the powerful LLMs from OpenAI and Google into an efficient architecture capable of achieving scalability, robustness, and cost-effectiveness while simultaneously matching the expectations of end users with a user-friendly experience.