Introduction In the evolving landscape of AI-driven applications, the ability to seamlessly connect large language models (LLMs) with external tools and data sources is becoming a cornerstone of in...

🚀 Introduction As AI copilots and assistants become integral to enterprises, one question dominates architecture discussions: “How can we make large language models (LLMs) provide accurate, sour...

Introduction In today’s enterprise landscape, enabling AI agents to interact with backend systems securely and at scale is critical. By exposing MCP servers through Azure API Management (APIM), org...

Voice is a natural interface for communication. Now, with the general availability of gpt-4o-transcribe-diarize, the new automatic speech recognition (ASR) model in Azure AI Foundry, transforming spe...

Azure Voice Live API recently reached General Availability, marking a significant milestone in conversational AI technology. This unified API surface doesn't just enable speech-to-speech capabilities...

Why Cost Optimization in Azure AI Services Matters? Cost optimization ensures that AI projects remain scalable, predictable, and sustainable, balancing innovation with financial responsibility. A...

Deploying large language models (LLMs) without rigorous evaluation is risky: quality regressions, safety issues, and expensive rework often surface in production—when it’s hardest to fix. This guide ...

In this blog post, we’ll explore the Voice Live API from Azure AI Foundry. Officially released for general availability on October 1, 2025, this API unifies speech recognition, generative AI, and tex...

Introduction Modern development workflows increasingly rely on secure integrations between tools and platforms. Copilot Studio, with its ability to extend functionality through MCP (Model Context P...