Production-Ready RAG: Build, Evaluate & Scale AI Systems for Enterprises

Why Should You Join?

Many AI projects look good in slides, but struggle when taken to production.

In this live session, we will break down how to build a Retrieval-Augmented Generation (RAG) system step by step and discuss what it takes to make it reliable for enterprises.

You’ll see how to evaluate its answers, reduce hallucinations, and monitor it in practice.

This Session is Best for You if:

✅ You want to understand how enterprises are actually using AI in 2025
✅ You’ve worked with RAG but want to know how to productionize it
✅ You’re curious about evaluation metrics, observability, and agents
✅ You want a practical demo, not just theory

This Session is Not for You if:

❌ You’re completely new to AI/LLMs (we won’t be covering basics of models)
❌ You only want toy projects, not enterprise-ready systems

What We’ll Cover:

• What’s happening in AI & what enterprises are building today and RAG
• Building a pipeline step-by-step: Ingestion → Chunking → Embeddings → VectorDB → Retrieval → Generation
• How to check if your system is grounded & reliable (Evaluations)

Pre-Requisites:

• You’ve worked with AI/LLM apps (even at a prototype level)
• You’re curious about taking them into production
• You’re comfortable with concepts like embeddings, prompting, and vector search