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Foundry AI

Building robust web agents requires reproducible testing, high-quality labels, and scalable evaluation.

Foundry AI

About Foundry AI

What is Foundry AI?

Foundry is a platform designed for building and evaluating browser agents. It allows users to configure tasks, define evaluation criteria, and collect high-quality data specifically for reinforcement learning (RL) and agent improvement. This platform is particularly beneficial for developers and researchers looking to enhance the performance of their web agents.

With Foundry, users can take advantage of a deterministic web simulator and an annotation framework, which facilitates the collection of labels, benchmarking of agents, and debugging of performance. This ensures that evaluations are conducted without the unpredictability associated with the live web, such as web drift, IP bans, or rate limits.

Reproducible web environments for fair agent evaluation

Scalable annotation for ground truth labels

Agent debugging and continuous improvement

Foundry AI Features

Foundry is a platform designed for building and evaluating browser agents, enabling users to configure tasks, define evaluation criteria, and collect high-quality data for reinforcement learning (RL) and agent improvement. This platform is particularly beneficial for creating robust web agents through reproducible testing and scalable evaluation.

Key features and capabilities of Foundry include:

Deterministic web simulation for consistent agent evaluation.

Scalable annotation framework for collecting ground truth labels.

Tools for debugging agent performance and facilitating continuous improvement.

Ability to benchmark agents without the unpredictability of the live web.

Why Foundry AI?

Foundry is a powerful platform designed for building and evaluating browser agents, offering users the ability to configure tasks and define evaluation criteria. This flexibility allows for the collection of high-quality data essential for reinforcement learning (RL) and the continuous improvement of agents. By utilizing Foundry, users can ensure that their agents are tested in a controlled environment, minimizing the unpredictability associated with live web interactions.

The advantages of using Foundry include:

Reproducible web environments that facilitate fair agent evaluation.

Scalable annotation tools for obtaining ground truth labels.

Robust debugging capabilities to enhance agent performance.

Continuous improvement processes without the risks of web drift, IP bans, or rate limits.

How to Use Foundry AI

To get started with Foundry AI, users can leverage the platform's capabilities for building and evaluating browser agents. The initial steps involve configuring tasks and defining evaluation criteria tailored to specific needs. This setup allows for the collection of high-quality data essential for reinforcement learning (RL) and agent improvement.

Foundry AI offers a range of features that enhance the user experience and facilitate effective agent evaluation:

Deterministic web simulation for reproducible testing.

Scalable annotation framework for collecting ground truth labels.

Tools for debugging agent performance and continuous improvement.

Ready to see what Foundry AI can do for you?[@portabletext/react] Unknown block type "span", specify a component for it in the `components.types` propand experience the benefits firsthand.

Key Features

Deterministic web simulator
Annotation framework for high-quality labels
Benchmarking agents
Debugging performance

How to Use

1

Visit the Website

Navigate to the tool's official website.

Pros & Cons

What's good

Reproducible web environments
Scalable annotation for ground truth labels
Continuous improvement of agent performance

What's not good

No cons listed

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