Build custom AI agents and applications

  • 4 minutes

When your organization requires full control over user experience, orchestration, or AI model behavior, building a custom AI agent or application may be the right approach. Microsoft offers a comprehensive set of tools across Power Platform, Microsoft 365, and Azure to support a wide range of development needs from low-code to pro-code, and from internal productivity agents to commercial generative AI applications.

Explore custom agents

Custom agents are fully customized from the model layer to the user experience and are built independently of Microsoft 365 Copilot.

Unlike declarative agents, custom agents can be deployed across multiple channels, including:

  • Microsoft Teams (as apps or bots)
  • Microsoft 365 Copilot experiences
  • Web and mobile applications
  • Company line-of-business systems

Custom agents offer advanced capabilities, including:

  • Advanced orchestration, workflow management, and multistep planning
  • Deep integration with external APIs, proprietary systems, and enterprise authentication
  • Flexible model selection, fine-tuning, and support for advanced AI techniques such as retrieval-augmented generation (RAG) and multimodal inputs/outputs
  • Custom memory, context management, and autonomous execution
  • Multiagent collaboration
  • Customizable user interfaces, branding, and user experiences beyond Copilot Chat
  • Enhanced security, compliance, monitoring, and analytics
  • Full control over hosting, scaling, and lifecycle management
  • Deployment across channels (Teams, web, mobile, and line-of-business apps)

Custom agent scenarios

Custom AI agents are typically built to address scenarios where out-of-the-box solutions are insufficient. Some common scenarios include:

  • Delivering customer-facing or commercial applications that require unique branding, workflows, or integrations.
  • Enabling multimodal data analysis, combining text, images, or other data types in a single conversational experience.
  • Supporting scalable, multichannel deployments across Teams, web, mobile, and line-of-business applications.
  • Automating internal productivity tasks, such as HR inquiries, IT support, or workflow management.
  • Building assistants for sales, customer service, onboarding, or guided training.
  • Orchestrating multiagent collaboration or managing complex, multistep workflows.
  • Developing industry-specific solutions for sectors like healthcare, finance, or manufacturing.

These scenarios often require advanced orchestration, deep integration, or custom user experiences that go beyond what declarative agents can provide.

Real-world examples of custom agents

Here are a couple of examples of how organizations have built custom AI agents to address specific business needs:

  • Healthcare Virtual Assistant: A healthcare provider developed a custom agent integrated with their electronic health record (EHR) system. The agent assists clinicians by retrieving patient information, scheduling appointments, and answering policy questions, all while maintaining compliance with healthcare regulations.

  • Financial Services Chatbot: A financial institution created a multichannel agent that helps customers with account inquiries, transaction histories, and personalized financial advice. The agent integrates with internal banking APIs and uses advanced orchestration to escalate complex cases to human advisors when needed.

When to build a custom agent solution

Consider building a custom agent when:

  • You need deep integration with proprietary systems or APIs
  • Your workflows require complex orchestration or business logic
  • You want to deliver a branded or embedded experience outside of Copilot Chat
  • You need to use custom models or advanced AI techniques like retrieval-augmented generation (RAG)
  • You want to enable autonomous agent capabilities, such as multistep planning and execution

Note

When building a custom agent or generative AI application, remember that in addition to configuring custom models and orchestration, you will also need to set up hosting for your solution using cloud services such as Azure or Copilot Studio, which may incur additional costs.

Security, compliance, and responsible AI

When building custom AI agents, it's important to ensure your solutions are secure, compliant, and aligned with responsible AI principles. Microsoft provides documentation and tools to help developers build secure, compliant, and responsible AI applications:

Custom agent development options and tools

Microsoft offers a variety of approaches for building custom agents and generative AI applications, including low-code and pro-code options.

Core development tools

  • Copilot Studio: Build low-code agents using natural language, Power Platform connectors, and automation—ideal for internal support, workflow automation, and guided assistants within Microsoft 365.
  • Azure AI Foundry: A unified platform and SDK for building, deploying, and managing enterprise-grade generative AI applications with full control over orchestration, model selection, and scaling.
  • Microsoft 365 Agents Toolkit: A Visual Studio Code extension that accelerates agent development for Microsoft 365 Copilot and Teams with templates, multi-environment support, and integrated debugging.
  • Visual Studio and GitHub: Use Visual Studio and GitHub to manage, test, and deploy AI agent solutions with full version control, CI/CD pipelines, and collaboration features.

Core services and SDKs

  • Foundry Agent Service: A managed runtime within Microsoft Foundry for orchestrating intelligent agents using LLMs, tools, and secure infrastructure—supporting thread management, tool invocation, and observability.
  • Microsoft 365 Agents SDK: A cross-platform SDK for building agents that run across channels including Microsoft 365 Copilot, Teams, and custom apps, with built-in scaffolding for communication and channel management.
  • Microsoft Teams SDK: Suite of packages for developing solutions on Microsoft Teams, including custom agents.

Orchestration frameworks

Use frameworks such as Microsoft Agent Framework, TaskWeaver, and Auto-Gen to orchestrate complex workflows, integrate multiple AI models, and enable advanced agent behaviors.

Note

Many solutions leverage a combination of these tools and services.

Reflection

Consider: Does your organization have requirements such as deep integration, advanced orchestration, or unique user experiences that go beyond what declarative agents offer? Reflect on your current and future needs to determine if building a custom agent solution is the right approach for your scenario.