Microsoft Foundry - previously known as Azure AI Foundry - is Microsoft’s platform for building, testing, deploying and governing AI applications and agents in Azure.
It brings models, development tools, business data connections, safety controls, monitoring and evaluation into one environment. For the right organisation, that can make it easier to move from an AI experiment to a managed business system. It is not, however, a simple replacement for Microsoft Copilot or ChatGPT, and many smaller businesses will not need it.
What is Microsoft Foundry?
Microsoft describes Foundry as a unified platform for building and governing AI applications and agents. A team can create a project, select or deploy an AI model, connect approved information sources, develop an application or agent, test how it behaves and monitor it after deployment.
You may still see the older names Azure AI Foundry and Azure AI Studio in articles, screenshots and parts of the Azure ecosystem. The current Microsoft documentation uses Microsoft Foundry.
What can a business build with it?
Foundry is intended for customised AI solutions rather than everyday standalone prompting. Examples include:
- An internal knowledge assistant that answers questions using approved policies, procedures or product documentation.
- A customer-service assistant that collects information, checks knowledge sources and passes complex cases to a person.
- A document-processing workflow that extracts, classifies or summarises information from forms and reports.
- A sales or account assistant that prepares briefing notes using permitted customer and product data.
- An operations agent that performs controlled tasks through approved tools and business systems.
- A specialist application that uses text, images, audio or structured business data.
The important distinction is that the organisation is building and operating its own solution. Foundry provides the platform and controls, but it does not remove the need for good process design, testing, security and ownership.
How does Microsoft Foundry work?
- Create a Foundry project. A project acts as a workspace for models, agents, evaluations, files and team access.
- Select a model. The available catalogue includes Microsoft and third-party models. Availability, hosting, terms and data handling can differ between models.
- Build the application or agent. Teams can work through the Foundry portal, software development kits, templates and development tools.
- Connect knowledge and tools. A solution can use approved files, search indexes, SharePoint, APIs, Azure Functions, Logic Apps or other services where suitable.
- Test and evaluate. Evaluation helps check quality, safety and whether the agent completes the intended task consistently.
- Deploy and monitor. Production systems need monitoring, access control, cost management and an agreed process for handling errors.
Microsoft Foundry, Copilot Studio or Microsoft 365 Copilot?
| Option | Best suited to | Typical requirement |
|---|---|---|
| Microsoft 365 Copilot | Employees working in Word, Excel, Outlook, Teams and other Microsoft 365 applications | Use AI within familiar productivity tools |
| Copilot Studio | Low-code or managed business agents, particularly in the Microsoft ecosystem | Create an agent with connectors and workflows without building everything from scratch |
| Microsoft Foundry | Development teams building customised AI applications and agents | Greater control over models, code, deployment, evaluation, monitoring and governance |
There is overlap, and the products can work together. The correct choice depends on the process you are improving, the systems and information involved, the skills available and how much control the organisation needs.
What are the advantages?
- Choice of models: teams can compare models rather than designing the whole solution around one option.
- Azure integration: Foundry can fit organisations already using Azure identity, security, monitoring and data services.
- Evaluation and observability: teams can test outputs, review traces and establish quality thresholds before wider release.
- Access control and project separation: roles and projects help control who can build, manage or use a solution.
- Enterprise deployment options: the platform supports development, hosted agents and production monitoring.
What should a business be careful about?
Cost is not one simple licence
Foundry services are generally consumption based. Charges can include model tokens, storage, search, tools, connections and hosted compute. A prototype that appears inexpensive can cost more when usage, connected services and monitoring increase. Set budgets, alerts and ownership before production use.
Data handling depends on the configuration
Model provider, deployment type, Azure geography, connected tools and external services can affect where information is processed and which terms apply. Do not assume every model in a catalogue has identical privacy arrangements.
An agent can take incorrect action
AI output can be inaccurate or inconsistent. Actions that affect customers, money, access, legal rights or important records should have strong controls and, where appropriate, human approval.
Connecting business information needs governance
An assistant should not reveal information merely because that information exists in a connected source. Permissions, document quality, retention, auditing and the principle of least privilege all matter.
A sensible way to start
- Choose one narrow business problem with a measurable outcome.
- Confirm why AI is appropriate instead of ordinary automation or search.
- Identify the information the solution needs and who is permitted to access it.
- Build a small proof of concept using non-sensitive or carefully controlled data.
- Create realistic tests, including incorrect, ambiguous and malicious requests.
- Measure quality, cost and time saved before expanding the solution.
- Document ownership, monitoring, incident handling and the ability to switch the service off.
Is Microsoft Foundry suitable for a small business?
It can be, particularly where a business has a specific process, technical support and an existing Azure environment. It may be excessive if the requirement is simply to summarise documents, draft emails or help individuals work more efficiently. In those cases, a Microsoft 365 Copilot licence, Copilot Studio solution or another established product may be faster and easier to manage.
Start with the business problem, not the platform. A successful project should improve a real outcome - such as response time, consistency or administrative effort - without creating disproportionate cost or risk.
Independent help with the decision
MyTechAdvisor can help you clarify the requirement, compare realistic options and identify the technology, licensing and implementation questions to resolve before committing to a platform.
Contact MyTechAdvisor about an AI or Microsoft cloud project or review our Managed IT Support service.
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