As generative AI moves from experimentation to enterprise deployment, ensuring trust, reproducibility, and safety becomes critical. This session explores how to design production-grade generative AI pipelines—from prompt engineering and output validation to bias mitigation and observability.

Attendees will learn how to integrate human-in-the-loop (HITL) workflows, metadata versioning, and feedback loops for improving generation quality. Real examples will showcase how enterprise teams in finance and customer service are using LLMs like GPT and open-source models to automate tasks, while enforcing ethical and business guardrails.

We’ll also discuss how to architect scalable, audit-ready GenAI workflows using Vertex AI, LangChain, and prompt versioning systems.