All news with #azure ai foundry tag

Prisma AIRS Integration with Azure AI Foundry for Security

🔒 Palo Alto Networks announced that Prisma AIRS now integrates natively with Azure AI Foundry, enabling direct prompt and response scanning through the Prisma AIRS AI Runtime Security API. The integration provides real-time, model-agnostic threat detection for prompt injection, sensitive data leakage, malicious code and URLs, and toxic outputs, and supports custom topic filters. By embedding security into AI development workflows, teams gain production-grade protections without slowing innovation; the feature is available now via an early access program.

Azure AI Foundry and UiPath: Agentic Automation in Care

🏥 Microsoft and UiPath describe how integrated agents from Azure AI Foundry and UiPath, orchestrated by UiPath Maestro, can operationalize AI within clinical workflows to surface and act on incidental radiology findings. The workflow uses UiPath medical record summarization agents to flag findings, Azure AI Foundry imaging agents to analyze PACS images and prior results, and UiPath agents to aggregate and forward consolidated follow-up reports to ordering clinicians. Microsoft says this agentic approach accelerates decision-making, reduces physician workload, and improves outcomes while maintaining compliance with DICOMweb and FHIR standards.

The Signals Loop: Fine-tuning for AI Apps and Agents

🔁 Microsoft positions the signals loop — continuous capture of user interactions and telemetry with systematic fine‑tuning — as essential for building adaptive, reliable AI apps and agents. The post explains that simple RAG and prompting approaches often lack the accuracy and engagement needed for complex use cases, and that continuous learning drives sustained improvements. It highlights Dragon Copilot and GitHub Copilot as examples where telemetry‑driven fine‑tuning yielded substantial performance and experience gains, and presents Azure AI Foundry as a unified platform to operationalize these feedback loops at scale.

OpenAI Sora 2 Launches in Azure AI Foundry Platform

🎬 Azure AI Foundry now includes OpenAI's Sora 2 in public preview, providing developers with realistic video generation from text, images, and video inputs inside a unified, enterprise-ready environment. The integration offers synchronized multilingual audio, physics-based world simulation, and fine-grained creative controls for shots, scenes, and camera angles. Microsoft highlights enterprise-grade security, input/output content filters, and availability via API starting today at $0.10 per second for 720×1280 and 1280×720 outputs.

Microsoft Agent Framework Brings Multi-Agent Tooling

🤖 The Microsoft Agent Framework is now in public preview inside Azure AI Foundry, offering an open-source SDK and runtime to simplify orchestration of multi-agent systems. Developers can prototype locally and deploy with built-in observability, durability, and compliance while integrating tools via OpenAPI, Agent2Agent (A2A), and the Model Context Protocol (MCP). Microsoft also previews stateful multi-agent workflows and has contributed multi-agent tracing standards to OpenTelemetry. Responsible AI controls and a generally available Voice Live API add governance and real-time voice capabilities for enterprise scenarios.

Microsoft Marketplace: Unified Cloud and AI Solutions

🚀 The reimagined Microsoft Marketplace is a unified destination to find, try, buy and deploy cloud solutions, AI apps and agents, combining Azure Marketplace and Microsoft AppSource. It lists tens of thousands of offerings and more than 3,000 AI apps and agents with rapid provisioning into Microsoft environments using Model Context Protocol (MCP). Integrations with CSPs and channel partners support private offers, a resale-enabled preview and governance for enterprise deployment.

Agent Factory: Building the Open Agentic Web Stack

🔧This wrap-up of the Agent Factory series lays out a repeatable blueprint for designing and deploying enterprise-grade AI agents and introduces the agentic web stack. It catalogs eight essential components—communication protocols, discovery, identity and trust, tool invocation, orchestration, telemetry, memory, and governance—and positions Azure AI Foundry as an implementation. The post stresses open standards such as MCP and A2A, emphasizes interoperability across organizations, and highlights observability and governance as core operational requirements.

Blueprint for Building Safe and Secure AI Agents at Scale

🔒 Azure outlines a layered blueprint for building trustworthy, enterprise-grade AI agents. The post emphasizes identity, data protection, built-in controls, continuous evaluation, and monitoring to address risks like data leakage, prompt injection, and agent sprawl. Azure AI Foundry introduces Entra Agent ID, cross-prompt injection classifiers, risk and safety evaluations, and integrations with Microsoft Purview and Defender. Join Microsoft Secure on September 30 to learn about Foundry's newest capabilities.

Agent Integration with Open Standards: MCP and A2A

🔗 Azure's Agent Factory blog emphasizes that interoperability is the key to moving agentic AI from isolated prototypes to enterprise-scale solutions. The post promotes open standards like Model Context Protocol (MCP) and Agent2Agent (A2A) to enable shared context, reusable tools, and cross-framework collaboration across runtimes such as Semantic Kernel. It explains how Azure AI Foundry combines these protocols with thousands of connectors, unified observability, and governance so agents can act across SaaS, legacy systems, and custom APIs without costly rewrites.

Agent Factory: From Prototype to Production with Foundry

🔧 Azure AI Foundry aims to accelerate the path from IDE prototypes to enterprise-grade AI agents. It emphasizes local-first prototyping, a single, consistent Model Inference API, and one-click deployment from VS Code and GitHub so developer code runs unchanged in production. Foundry supports popular frameworks like Semantic Kernel and AutoGen, embraces open protocols (MCP, A2A), and supplies prebuilt connectors, observability, and enterprise guardrails to scale agents securely.

Agent Factory: Top 5 Agent Observability Practices

🔍 This post outlines five practical observability best practices to improve the reliability, safety, and performance of agentic AI. It defines agent observability as continuous monitoring, detailed tracing, and logging of decisions and tool calls combined with systematic evaluations and governance across the lifecycle. The article highlights Azure AI Foundry Observability capabilities—evaluations, an AI Red Teaming Agent, Azure Monitor integration, CI/CD automation, and governance integrations—and recommends embedding evaluations into CI/CD, performing adversarial testing before production, and maintaining production tracing and alerts to detect drift and incidents.