The Model Context Protocol (MCP) has been rapidly gaining traction, going viral on social media over the past two weeks. The community has already built dozens of MCP servers across a wide spectrum of domains, extending LLM capabilities with external tools, services, and data sou...

Making AI Work for Your Data AI agents are becoming active participants in data management. Nowadays instead of writing SQL queries, you can simply ask and chat with your data “Show me all shipments currently in transit.” Or even better, AI agents can act on your data “Create a n...

When you are building chat applications for internal teams or customer support, you need to isolate data to meet data residency and compliance requirements. Also, you want to chat with internal documents or APIs securely and safely. You can’t rely on public AI services like ChatG...

Retrieval Augmented Generation (RAG) works by taking a user’s question, searching for information relevant to that question, and then including the retrieved information alongside the question in a prompt to an AI chat model ChatGPT/Claude/DeepSeek, please answer question X using...

As vector search and Retrieval Augmented Generation(RAG) become mainstream for Generative AI (GenAI) use cases, we’re looking ahead to what’s next. GenAI primarily operates in a one way direction, generating content based on input data. Generative Feedback Loops (GFL) are focused...

This blog explains how to build an AI powered email Assistant that can draft, edit, and send emails, store them as vector embeddings, and retrieve similar emails using contextual search. The assistant leverages Semantic Kernel for AI operations, Neon for vector storage, and Azure...