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In this video, we’re hardening our RAG architecture to meet the demands of the enterprise!

Building on our previous video (   • Implement #RAG (Retrieval Augmented Genera...  ), we are making our RAG for Microsoft Fabric enterprise grade.

Link to our blog for the code used in this video: https://www.obvience.com/blog/enterpr...

In this video, we explore the intricate details of building a Retrieval-Augmented Generation (RAG) architecture that meets enterprise standards. Whether you're a novice or looking to deepen your technical knowledge, this video is for you!

*Timestamps:*
00:00 - Introduction
00:25 - Series Overview
01:04 - Why RAG and Its Importance
02:45 - Understanding LLM Limitations
04:33 - Integrating RAG with Enterprise Data
06:47 - Vector Databases Overview
08:05 - Comparison: Azure AI Search, Chroma DB, and Cosmos DB
09:37 - Introduction to DiskANN
10:29 - Practical Configuration Guide
14:02 - Managing Knowledge Bases
20:00 - Storing and Querying Data
24:32 - Running SQL Queries in Cosmos DB
26:39 - Advantages Over Chroma DB
29:56 - Future Directions and Reflections
31:04 - Conclusion and Request for Feedback
33:56 - Call to Action: Like and Subscribe

🔍 What You'll Learn:

Why RAG? Understanding the need and purpose behind RAG.
Handling Limitations: Addressing inherent limitations of LLMs (Large Language Models).
Technical Walkthrough: Step-by-step guide on configuring and implementing RAG.
Tool Selection: Choosing the right tools from the Microsoft stack, with a focus on Cosmos DB over ChromaDB and Azure AI Search.
Vector Databases: Utilizing vector databases for efficient and meaningful searches.
Hands-On Demo: Live demonstration with code snippets, making it easy to follow along.
This video dives deeper than the previous ones, covering configurations and tools in detail. Even if you missed the earlier videos, this one starts from scratch and provides all the necessary information.

💡 Key Topics:
Introduction to RAG and its significance
Addressing limitations of LLMs with RAG
Step-by-step guide on using Cosmos DB and DiskANN
Practical configuration tips and tricks
Comparisons of different tools: Azure AI Search, Chroma DB, and Cosmos DB
How to manage knowledge bases effectively

Don't forget to like, subscribe, and share your feedback! Would you prefer shorter videos or more detailed deep dives? Let us know in the comments.