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Foundry

Foundry provides a powerful platform for developing AI agents that interact with websites. It offers advanced browser simulation, detailed action tracking, and custom data generation to help train agents, making them more reliable and faster to evaluate in real-world enterprise environments.

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OverviewFeaturesUse CasesFAQ

About Foundry

Who It's For

Foundry is for developers creating AI agents that browse websites. It helps make these agents reliable and accurate on web platforms. This tool is perfect for businesses needing precise testing and data to train their web-focused AI.

What You Get

You get flawless browser simulations, free from internet issues. Foundry tracks every agent action, flagging mistakes like failed clicks. It also provides custom, expertly-made datasets to fine-tune your AI browser agents for real tasks on company websites.

How It Works

Connect Foundry to your AI agent tools with a simple Python kit. It creates realistic browser environments for agents to train. All agent actions are recorded, providing clear insights. This speeds up training, ensuring AI agents perform well on enterprise platforms.

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Features & Capabilities

⚙️ Core AI Agent Platform

Reproducible Browser Simulation

Provides pixel-perfect, consistent browser environments without performance or rate limiting issues.

Comprehensive Agent Evaluation

Tracks and classifies every agent action, ensuring all failures and misfires are identified.

Scalable RL Agent Training

Enables safe sampling and evaluation of unlimited trajectories for training browser agents at scale, free from anti-bot constraints.

📊 Data & Development Tools

Custom Dataset Generation

Generates custom, long-horizon datasets through expert annotation for agent fine-tuning on real enterprise platforms.

Python SDK Integration

Seamlessly integrates Foundry into existing agent workflows using a powerful Python SDK.

Use Cases

Generating High-Fidelity Training Data for Web Automation Agents

Developers building AI agents for complex web tasks often struggle to acquire sufficient, high-quality training data. Foundry provides expert-annotated, long-horizon datasets specifically for fine-tuning browser agents on real enterprise platforms, ensuring agents learn from authentic interactions and reducing development cycles.

B2B SaaS, Enterprise AutomationFor: AI Engineers, Machine Learning Developers, Data Scientists

Rigorous Evaluation and Quality Assurance for Browser AI Agents

Ensuring AI agents reliably perform tasks in dynamic web environments is critical for enterprise applications. Foundry offers pixel-perfect, reproducible browser simulations and detailed tracking of every agent action, enabling developers and QA teams to detect and diagnose failures like layout shifts or misfires before deployment, leading to more robust and dependable agents.

Software Development, Quality AssuranceFor: QA Engineers, AI Engineers, Automation Specialists

Scalable Development and Management of Enterprise AI Agent Deployments

Enterprises require a unified platform to build, fine-tune, and orchestrate various AI agents efficiently. Azure AI Foundry offers a comprehensive environment for managing models, deploying agents, and monitoring performance, providing the foundational infrastructure for integrating specialized tools like Foundry's web simulation capabilities to scale AI automation across the organization.

Enterprise Software, IT, Cloud ServicesFor: AI Architects, DevOps Engineers, Go-to-Market Leaders

Accelerating Iteration and Experimentation for AI Agent Workflows

AI developers often need to rapidly test new agent behaviors and prompts to optimize performance and achieve desired outcomes. By combining Foundry's fast evaluation cycles in controlled, reproducible simulation environments with Azure AI Foundry's built-in playgrounds and prompt engineering tools, teams can quickly prototype, experiment, and refine agent logic, significantly shortening the development feedback loop.

Software Development, R&DFor: AI Developers, Prompt Engineers, Data Scientists

Frequently asked questions

Azure AI Foundry is Microsoft's platform for building, managing, and deploying generative AI solutions. It provides a unified environment to experiment with, fine-tune, and deploy large language models (LLMs) and AI agents, with integrated tools for prompt engineering, agent orchestration, and monitoring.

Azure OpenAI gives access to advanced language models from OpenAI, while Azure AI Foundry Models extends this by providing access to a broader catalog of flagship models (including Azure OpenAI, Cohere, Mistral AI, Meta Llama, AI21 Labs, etc.) under the same service, endpoint, and credentials, allowing you to switch between models without changing your code.

Azure AI Services are prebuilt APIs for common AI scenarios (like vision, speech, translation), whereas Azure AI Foundry is a platform that includes Azure AI Services and adds capabilities for deploying and managing LLMs, building agents, and orchestrating AI workflows.

Azure AI Foundry is available in most regions where Azure AI services are available. For specific details, check the region support documentation.

Yes. Azure AI Foundry supports seamless access to data in Microsoft Fabric Lakehouse and can access data from Amazon S3 buckets via Fabric shortcuts without copying data.

Azure AI Foundry offers a model catalog with foundational models (GPT, Llama, Mistral, etc.), fine-tuning and deployment of models (serverless or managed), an agent service for building and orchestrating AI agents, built-in playgrounds for testing models and agents, integration with external APIs and tools via Model Context Protocol (MCP), prompt engineering and reusable prompt templates, security, compliance, and governance tools, and monitoring and observability for AI applications.

To set up Azure AI Foundry, log in to the Azure portal, navigate to Azure AI Foundry under AI services, create a new project, select a region, and choose a resource group, then add models and tools from the catalog or upload your own.

Yes. You can fine-tune your own models or use Azure’s pre-built models with your own datasets.

MCP is a standardized protocol in Azure AI Foundry that allows you to extend agents with custom tools, prompts, and resources.

Yes. The Foundry Agent Service is stateful and retains data. There are two types of data: user data and system data. For details, refer to the Agent Service FAQ.

Azure AI Foundry provides centralized observability, application tracing, execution flow views, and automated evaluations for AI outputs. You can set up alerts and reporting based on metrics like relevance, groundedness, and fluency.

Yes. You can use hubs to share models, prompts, and tools across teams and projects.

Tags

web automationagent trainingdata generationagent evaluationreinforcement learning

Specifications

Deployment
Browser
API
Cloud
Target Audience
Startup
Enterprise
Complexity
Expert

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