Getting an AI agent to run in production has always been harder than building it. The prototype works on your laptop, but then the questions start: where do I host…
If you have ever put a generative AI application into production, you know the feeling: the solution works beautifully in the POC, and when volume grows, the token bill becomes…
One of the biggest fears when adopting generative AI is hallucination: the model gives an answer that sounds convincing but is wrong. The good news is that you can drastically…
Language models know how to converse — but, on their own, they do not query your database, read the company document index, or trigger actions in the real world. That…
When it comes to organizing a lakehouse, the Medallion architecture has become the market standard in Databricks. It solves a classic problem: how to transform raw, messy data into reliable…
If you work with generative AI, you have already heard of RAG. But what is RAG in practice — and why has it become the standard for making language models…
Introduction The RAG (Retrieval-Augmented Generation) architecture represents a new approach to building generative AI applications that use company-specific information. Instead of relying only on the static knowledge of a large…
Data Warehouse Architecture with Microsoft Azure Let's explore "Data Warehouse Architecture with Microsoft Azure" in detail, a modern approach to storing and analyzing large volumes of data. I will guide…
Kappa Data Architecture with Microsoft Azure we dive into "Kappa Data Architecture with Microsoft Azure", an efficient approach to continuous real-time data processing. Kappa architecture eliminates the need for batch…
Lambda Data Architecture with Microsoft Azure Want to understand how Lambda architecture can transform the way your company processes data in real time and in batch? I have just released…