23 posts
Foundry IQ's pitch is that your agents get one endpoint for grounded, cited, multi-source context instead of a hand-rolled retrieval stack. !banner What doesn'...
Your largest corpus is the one nobody indexed. Here's how to turn recordings into grounding data an agent can cite. --- The corpus you already have and never in...
This guide walks through the setup, MCP response parsing, long-lived Entra token refresh, per-user permission filtering, citation handling, and how to avoid conflicts between LangGraph’s planner and Foundry IQ’s agentic retrieval planner.
Every recorded meeting your organization has ever held is already a knowledge base. It just happens to be stored in the least queryable format imaginable, which...
Most agents are billed for tools they don't use. Not once — on every single turn. The mechanics are simple enough that it's easy to miss. When you give a model ...
Why "search" isn't enough anymore A plain RAG pipeline — embed a query, hit a vector index, stuff the top-k chunks into a prompt — works fine for a single-turn ...
Most "RAG tutorials" stop at a single embedding query against a single index. That works for a demo and falls over the moment a real user asks something like "c...
This closes out the series' capstone: the multi-agent customer support system built across Parts 6-9, now hardened with evaluation, cost governance, and observa...
Azure AI Foundry has a genuinely great portal. You can see your agent runs, the tools it called, the messages it sent and received, and even a breakdown of toke...
Once your multi-agent system (Parts 6-8) is functionally solid, the question that comes up in every enterprise security review is the same: how do you know an a...
Foundry IQ is Microsoft Foundry's managed knowledge-base layer, built on Azure AI Search under the hood, adding automatic freshness handling and simplified hybr...
Discover how Azure AI Search optimizes enterprise RAG using hybrid retrieval, semantic ranking, and integrated vectorization for production-ready AI apps.
Once you've decided a workload belongs in Foundry Agent Service (Part 6), the next problem is orchestration mechanics: multiple agents that need to share state,...
Explore the architecture and implementation of Azure AI Foundry Agent Service for building secure, scalable, and autonomous enterprise-grade AI agents today.
This is the decision that most often gets made by default (whichever tool the first prototype happened to use) rather than deliberately — and it's expensive to ...
Function-calling demos work because the model is well-behaved and the test queries are clean. Production breaks this in three specific ways: malformed arguments...
AzureML SDK v1 reaches end-of-support on June 30, 2026. CLI v1 already hit end-of-support in September 2025. If you have production pipelines built on azureml-s...
At Ignite 2025 (November 18), Microsoft renamed Azure AI Foundry to Microsoft Foundry — the second rename in twelve months after Azure AI Studio became Azure AI...
The transition from experimental generative AI (GenAI) prototypes to production-grade enterprise applications represents one of the most significant hurdles for modern cloud architects. While the indu...
LangGraph gives you fine-grained control over agent state and routing logic in code. Microsoft Foundry gives you managed hosting, identity, tracing, and one-cli...
A Prompt Flow DAG that passes every test case in the Foundry portal can still fail in production in ways that are maddening to reproduce — because the failure m...
If you've already shipped a first RAG pipeline in Azure AI Foundry, you've probably hit the point where "it works on the demo doc" stops being good enough. This...
The landscape of enterprise computing is undergoing its most significant shift since the migration to the cloud: the integration of generative artificial intelligence into the core of business operati...