Microsoft Unveils Azure AI Foundry: A Unified Platform for Enterprise AI Development

Azure AI Foundry tools for changes in AI applications

The way we use artificial intelligence is changing. Chatbots aren't going away. We'll continue to use them to deliver basic, natural language, self-service applications. But the future belongs to multimodal applications, built on large language models (LLMs) and other AI models, that act as self-organizing software agents. These more complex AI applications will require more thought, more code, more testing, and more safeguards. An AI evolution requires a similar evolution in our development tools. Although we've seen Power Platform's Copilot Studio begin to deliver tools for building task-focused agents, more complex AI applications will require a lot more work, even with support from frameworks like Semantic Kernel. Much of Azure's current AI tools, beyond its Cognitive Services APIs, are focused on building grounded chatbots, using Microsoft's Prompt Flow framework to add external vector indexes to LLMs for retrieval-augmented generation (RAG), along with wrapping calls and outputs in its own AI safety tools. It's a proven approach to building and running Microsoft's own Copilot services, but if enterprises are to get the next generation of AI services, they need new tools that can help deliver custom agents.

Microsoft brings together its enterprise AI offerings in the Azure AI Foundry

At its annual Ignite conference, Microsoft on Tuesday announced the Azure AI Foundry, a new offering that brings together a number of Microsoft's existing AI services for enterprises under a single umbrella. Azure AI Studio, Microsoft's hub for building generative AI-based applications, is the management console and portal for the AI Foundry. "Business leaders are looking to reduce the time and cost of bringing their AI solutions to market while continuing to monitor, measure and evaluate their performance and ROI. Which is why we're excited to unveil Azure AI Foundry today as a unified application platform for your entire organization in the age of AI," writes Jessica Hawk, Microsoft's corporate vice president for Data, AI, and Digital Applications. "Azure AI Foundry helps bridge the gap between cutting-edge AI technologies and practical business applications, empowering organizations to harness the full potential of AI efficiently and effectively." The Foundry will include Microsoft's model catalog, with closed and open weight foundation models, task models, and specialized industry models. The service combines these with existing Azure AI tools like Azure AI Search, AI Agents, AI Content Safety, and Azure Machine Learning. New here is the Azure AI Foundry SDK, which is now in preview and which provides a unified toolchain for "customizing, testing, deploying and managing AI apps and agents with enterprise-grade control and customization," according to Microsoft. Microsoft will offer developers 25 prebuilt app templates that will help them integrate the AI services into their own applications. The portal (previously Azure AI Studio) will be where developers can find and evaluate AI models, services, and tools, as well as a new management center that Microsoft says will help teams "manage and optimize AI apps at scale, including resource utilization across multiple hubs and subscriptions, access privileges and connected resources." It's basically a nice dashboard. And since no AI announcement in late 2024 is complete without mentioning agents, Microsoft is also including the Azure AI Agent Service in this package (or it will when it launches next month). This will enable developers to orchestrate multiple AI tools to build agents that can automate business processes. It will include features like bring-your-own-storage and private networking to keep private business data private. "In a market flooded with disparate technologies and choices, we created Azure AI Foundry to thoughtfully address diverse needs across an organization in the pursuit of AI transformation," Hawk writes. "It's not just about providing advanced tools, though we have those, too. It's about fostering collaboration and alignment between technical teams and business strategy."

Microsoft's Azure AI Foundry unifies AI development so everyone can get involved - SiliconANGLE

Microsoft's Azure AI Foundry unifies AI development so everyone can get involved Microsoft Corp. said today it wants to change the game for artificial intelligence development by providing everyone with the tools to implement cutting-edge AI capabilities within their business applications, and key to this is the launch of the new Azure AI Foundry. It's a brand-new offering announced at Microsoft Ignite 2024 that's meant to simplify the development and management of AI applications. It does this by "unifying the AI toolchain" within a new Azure AI Foundry software development kit that brings Azure AI capabilities to familiar developer tools such as GitHub and Visual Studio. The idea with Azure AI Foundry is that everyone within an organization - not just developers and AI engineers, but also information technology professionals and even regular workers - will be able to customize, host, run and manage AI with more confidence, so everyone can play a part in driving AI-powered innovation. Developers will benefit from more streamlined access to Microsoft's latest AI development innovations, while business leaders and IT pros will gain access to tools that provide more insights into the impact of AI on their business, the company said. Azure AI Foundry unifies all of the capabilities found within the existing Azure AI Studio with various new tools and services, including AI Agent Service, which is a new platform for creating "AI agents" that can perform tasks on behalf of human workers with minimal supervision. AI agents are all the rage these days, with companies such as Salesforce Inc. and ServiceNow Inc. racing ahead in their development, providing tools that can automate customer service requests and marketing outreach, for instance. Microsoft wants to help customers build even more advanced AI agents to automate yet more business processes. They'll be able to do this using AI Agent Service, which makes it easy to connect enterprise data sources like Microsoft Fabric and Microsoft SharePoint to new agents to ensure they're grounded in corporate knowledge. It also supports private networking and bring-your-own storage, ensuring data privacy and compliance for sensitive data. In addition to building AI agents, Microsoft Azure AI Foundry will also make it easier to monitor their performance with a new management center experience that brings key subscription information, such as connected resources, quota usage and access privileges, for each model, into a single pane of glass. To build AI agents, teams will need access to the most powerful AI models, and Microsoft is ensuring that with an expanded catalog that contains the latest large language models from companies like OpenAI, plus its own Phi family of small language models. It's also packed with various open-source and frontier models, including new ones from companies such as Bria Artificial Intelligence Ltd., NTT Data Corp. and Gretel Labs Inc. In addition, there are new industry-specific LLMs from companies like Bayer AG, Sight Machine Inc. and Paige.ai Inc., among others. And there's a new serverless provisioned deployment option for "models-as-a-service"-based models from companies like Meta Platforms Inc., Mistral AI, Hugging Face Inc. and Cohere Inc. Customers will also be able to better fine-tune those new models, with new capabilities from partners like OpenAI that enable vision fine-tuning and distillation, which paves the way for smaller models like GPT-4o mini or Phi to replicate the behavior of much larger LLMs, so users can create powerful AI applications with a much smaller footprint. Microsoft Azure AI Foundry also provides access to an expanded library of tools for evaluating and benchmarking these models, plus a unified model inference application programming interface, which makes it simpler to experiment with and compare various models. Using this, it becomes possible to more easily swap out models in existing AI applications, so they can be improved over time. Finally, there are new customization tools from providers including Gretel Labs, Weights & Biases Co. and Scale AI Inc., the company said. Microsoft's retrieval-augmented generation or RAG capabilities are getting a boost too. RAG is the technique that's used to funnel proprietary data to pretrained LLMs and SLMs so they can come up with more precise, up to date and contextual responses to questions. So a customer service chatbot can be linked to a company's internal knowledge base to better answer questions about their product return policy, for example. The Azure AI Search platform, which provides these RAG capabilities, now has a generative query engine available in select Azure regions to enhance performance, while Query Rewriting is a new capability in preview that's able to create multiple versions of a user's query to provide better responses. There's a new semantic ranker tool as well, which helps to rank those responses. Microsoft reckons these updates provide up to 12.5% better relevance, with responses delivered 2.3 times faster than before, translating to more responsive and more capable RAG-based AI models. Other new features found in the Azure AI Foundry include more advanced vector search and RAG capabilities in Azure Databases and GitHub Models, plus a preview of GraphRAG in Azure Database for PostgreSQL for private datasets. Then there's DiskANN, a new suite of algorithms for vector search available now in Azure Cosmos DB and in preview for Azure Database. There are additional responsible AI tools too, centered on AI reports and risk and safety evaluations for AI-generated images, to improve safety and compliance. Collaborations with Credo AI Inc. and Saidot Inc. give customers access to comprehensive AI governance platforms, Microsoft said. Additionally, Microsoft unveiled a new tool called Azure AI Content Understanding that can help developers to create cost-effective multimodal applications that understand text, audio, images and video inputs. Finally, the company lifted the lid on Azure Container Apps serverless graphics processing units, a new deployment option for serverless infrastructures. In a blog post, Jessica Hawk, Microsoft's corporate vice president of data, AI and digital applications, said the innovations in Azure AI Foundry will help more companies to get started in AI at a time when many continue to struggle to do so. She cites data from Deloitte Touche Ltd., which shows that 70% of organizations have only been able to move 30% or less of their generative AI experiments into production due to the difficulties involved. She cites data from Deloitte Touche Ltd., which shows that 70% of organizations have moved 30% or less of their generative AI experiments into production. It's for this reason that Azure AI Foundry comes with comprehensive guidance for AI adoption and architectures within Azure Essentials -- essentially, all of Microsoft's best practices, product experiences, reference architectures and other resources, in a single portal. "As AI transforms industries and unveils new opportunities, we're committed to providing practical solutions and powerful innovation to empower you to thrive in this evolving landscape," Hawk said. "Everything we're delivering today reflects our dedication to meeting the real-world needs of both developers and business leaders, ensuring every person and every organization can harness the transformative power of AI."

Microsoft launches Azure AI Foundry with agent orchestration, management tools

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Microsoft introduced AI agents to its Dynamics 365 platform in October. During Ignite, the company announced it would add more agentic AI capabilities to other Microsoft products, such as SharePoint and Microsoft Copilot 365. However, enterprises will need to manage the many AI agents they deploy and understand whether these agents accurately follow workflows and can only access what they are supposed to access. Microsoft's new capabilities in Azure AI aim to help developers build evaluation tools and a way to manage AI agents at scale and solve precisely those issues. The software developer kit for Azure AI Foundry offers a toolkit to customize, test, deploy and manage AI applications and agents. It lets developers bring control and customization to many AI apps brought into their tech stack. Microsoft said the SDK, available in preview, has 25 templates developers can use with an integrated library of models to build in scale. The Azure AI Foundry portal, formerly Azure AI Studio and also in previews, offers developers a visual dashboard for evaluating models and tools. The dashboard also lets people manage who can use certain apps. The company said AI Foundry is integrated with other developer tools like GitHub, Visual Studio and Copilot Studio. As agents become a more significant part of the AI ecosystem, enterprises want to figure out how to manage how these work together. Azure AI Agent Service lets companies establish orchestration frameworks for automated workflows. "With features like bring your own storage and private networking, it will ensure data privacy and compliance to help organizations protect their sensitive data," the company said. Agent management AI agents emerged as one of the big trends in enterprise AI this year and are poised to grow in the next year as more companies begin experimenting with them. Several providers, like Microsoft and Salesforce, offer customers access to agents or a no-code way of building agents. Microsoft is also researching how multiple agents can work together through a new framework called Magentic-One. Ideally, AI agents would automate workflows without requiring human employees to keep prompting AI applications. Companies are beginning to use multiple agents, triggering each activity to build out their agent ecosystems. To ensure the agents do their jobs, some providers create orchestration agents that monitor and direct agents. However, enterprises still need to figure out the best way to deploy these agents across their entire organization without accidentally letting agents access data they shouldn't. Determining safety and performance for agents can also be difficult, as current benchmarks don't really capture agentic performance.

Microsoft rebrands Azure AI Studio to Azure AI Foundry

The toolkit for building generative AI applications has been packaged with new updates to form the Azure AI Foundry service. Microsoft is packaging its Azure AI Studio and other updates into a new service -- Azure AI Foundry in response to enterprises' need to develop, run, and manage generative AI applications. Launched at the company's annual Ignite conference, Azure AI Foundry is being marketed as a "unified application platform in the age of AI," akin to the Azure AI Studio, which was released in November last year and made generally available in May this year. Azure AI Studio was developed and marketed by Microsoft as a generative AI application development platform with support for model filtering, model benchmarking, prompt engineering, retrieval augmented generation, agent building, AI safety guardrails, and to an extent low-code development.