Microsoft Foundry is a unified, interoperable platform for building, optimizing, and governing AI applications and agents at scale. It’s designed primarily for professional developers and technical teams who want to:

• Develop and fine-tune custom AI models.
• Access a large catalog of AI models (more than 11,000 models), including open-source, industry, and frontier models from providers such as OpenAI, Anthropic, DeepSeek, and Meta.
• Orchestrate and monitor agentic workflows using open agent frameworks.
• Rely on built-in quality, safety, and security controls for production-grade AI.

In Forrester’s composite example, Foundry is used by a global organization with $10 billion in annual revenue, 25,000 employees, and about 100 technical staff actively building and managing AI applications and agents. Typical users include developers, data scientists, ML engineers, data engineers, solution architects, IT admins, and security professionals.

Foundry brings together several services in one modular platform, including:

• Foundry Agent Service – to build, host, and scale AI agents (including multiagent solutions).
• Foundry Models – to discover and use a broad library of third-party and open-source models.
• Foundry IQ – to provide a knowledge layer for agents using next-generation retrieval augmented generation (RAG).
• Foundry Tools – to connect tools, data, and services for agentic apps.
• Azure Machine Learning – to build, train, and fine-tune models.
• Foundry Control Plane – to centralize identity, policy, observability, and security signals across AI workloads.

According to a Total Economic Impact study by Forrester (commissioned by Microsoft), organizations using Microsoft Foundry see a mix of cost savings, productivity gains, and new revenue opportunities.

For a composite global organization with $10 billion in revenue and 25,000 employees, the three-year, risk-adjusted results were:

• Total benefits (PV): $49.5 million
• Total costs (PV): $11.6 million
• Net present value (NPV): $37.9 million
• ROI: 327%
• Payback period: about 6 months

Key quantified benefit areas included:

• Technical team productivity: 35% improvement by Year 2, worth about $15.7 million over three years. Teams build AI apps and agents faster using a single platform, reusable templates, coding assistance, and model leaderboards.
• Streamlined operating expenses: about $17.2 million in savings over three years, driven by AI agents (roughly two-thirds focused on process automation) that reduce operating costs by around 10% in targeted expense categories.
• Faster time to market: about $17 million in incremental profit over three years by bringing AI-enabled products and services to market sooner.
• End-user productivity: around 10% productivity improvement for business users, worth $4.8 million over three years. About one-third of agents focus on human assistance, helping employees retrieve information and get recommendations so they can spend more time on higher-value work.
• Avoided legacy costs: about $4.3 million over three years by decommissioning prior AI infrastructure, tools, and related support.

On the cost side, the same composite organization incurred:

• $8.2 million in Foundry consumption costs over three years (depending on services and models used).
• $3.4 million in implementation and ongoing maintenance over three years, including a two-month pilot/rollout and about five FTEs to maintain the platform.

Beyond the quantified numbers, organizations also reported:

• Improved AI model quality and easier fine-tuning/grounding with the right data.
• Increased product and service innovation and improved customer experience and retention.
• Reduced costs by decommissioning legacy tools and simplifying infrastructure management.

Security, privacy, and governance are central reasons organizations choose Microsoft Foundry, based on the Forrester study. Many decision-makers cited concerns about open-source models, hidden vulnerabilities, and fragmented security controls before adopting Foundry.

Foundry is designed to help you reimagine AI development with enterprise-grade safeguards built in:

• End-to-end governance: Foundry Control Plane provides organization-wide observability and control over AI agents, models, and tools. This helps you enforce consistent identity, policy, and security across the AI lifecycle.
• Model scanning and guardrails: Foundry scans third-party and open-source models for emerging threats and vulnerabilities. It also offers configurable guardrails to manage inputs and outputs, so you can align model behavior with your policies.
• Embedded security and compliance: Security and compliance controls are integrated into the platform and workflows, which accelerates production readiness. Interviewees noted that this helped them move from experimentation to production with more confidence.
• Agent observability and control: With Foundry Agent Service, teams can orchestrate multiagent solutions and track and monitor agent behavior, which is especially important for complex, agentic AI use cases.

In the Forrester survey of 154 AI decision-makers using Microsoft Foundry, concerns about AI security, privacy, and governance were the top reasons organizations decided to adopt the platform. By centralizing security and governance and offloading infrastructure management to Microsoft, teams can focus more on building AI solutions while maintaining control over risk.