Foundry is a platform 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. Learn more at Foundry's website.
The core of Foundry’s platform is a deterministic web simulator paired with an annotation framework. This allows users to collect labels, benchmark browser-based agents, and debug agent performance without the typical obstacles of web drift, IP bans, or rate limits. The system is designed to streamline the agent development lifecycle by ensuring consistency and reproducibility in both the environment and data collection process.
Foundry addresses common challenges in reinforcement learning and web agent research by:
- Providing a controlled, repeatable environment for browser agents
- Facilitating the creation and evaluation of complex web-based tasks
- Supporting high-quality data labeling and benchmarking
These features make it possible to systematically improve agents and reliably compare results, which is critical for organizations and researchers working on web automation, AI agents, or RL applications that interact with web interfaces.
How Does Foundry Work?
Foundry enables users to set up web-based tasks that browser agents must complete. The deterministic simulator ensures that every agent interaction is consistent, eliminating the unpredictability of live web testing. The integrated annotation framework allows for efficient data labeling and performance evaluation, supporting better benchmarking and debugging of agent behaviors.
Who Uses Foundry?
While specific customer names are not provided, Foundry is best suited for AI researchers, machine learning engineers, and organizations focused on developing or evaluating browser automation agents and reinforcement learning systems. It is particularly useful for teams seeking to improve agent performance, collect reliable training data, or test agents against established benchmarks in web environments.
What Makes Foundry Different?
Foundry’s main differentiator is its deterministic web simulator, which ensures repeatable experiments and removes common blockers like web drift and rate limits. This focus on reproducibility and high-quality data collection helps users avoid issues that typically arise when training or testing agents on live web pages.
Recent Developments at Foundry
As of February 2024, Foundry published insights on benchmarking AI web agents, highlighting metrics, strategies, and challenges in the field. Their blog post (How to Benchmark AI Web Agents) offers guidance on handling website changes and improving reproducibility for accurate evaluations.
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