Discover and explore the most popular open source AI and machine learning tools from GitHub
The core library of differential privacy algorithms powering the OpenDP Project.
Toolbox for diagnosing bias in machine learning models
Tensorflow's Fairness Evaluation and Visualization Toolkit
Microsoft SEAL 4.X For Python
detect demographic differences in the output of machine learning models or other assessments
Fairness evaluation environment for machine learning
A command line tool to easily add an ethics checklist to your data science projects.
Low-level Python library used to interact with a Substra network
The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).
Xaynet represents an agnostic Federated Machine Learning framework to build privacy-preserving AI applications.
Python code for training fair logistic regression classifiers.
Python Accumulated Local Effects package
Building a responsible AI marketplace is a community effort. We're grateful to the developers, researchers, organizations, evaluators, and individuals whose work helps make AI more accessible, transparent, and responsible through the framework of 6 pillars:
Researchers and developers whose data collection efforts help build the foundation of AI tools.
Responsible AI Marketplace Open-source AI Tools Database
Cornell University
Advisor: Martin Wells
Contributors: Houlin Chen, Xinyu Zhu, Yinghan Xia, Kate Chanpong, Zixuan Huangfu
Responsible AI depends on meaningful evaluation, testing, research, and transparency.
Credits, resources and support.
Core technologies powering the marketplace.
Our marketplace is strengthened by the people who review, test, evaluate, document, and share their experiences with AI tools. Thank you to everyone who contributes their time, expertise, and perspective.
If you use this database in your research, please use the following BibTeX entry.
@misc{ai2030-marketplace,
title={AI2030 Responsible AI Open-Source Tools and Commercial Tools Database / Marketplace},
author={AI2030 and Community Contributors},
year={2025--2026},
url={https://marketplace.ai2030.org}
}A Note on Independence — Recognition on this page does not constitute an endorsement of a tool, organization, model, or viewpoint. Commercial relationships and sponsorships are disclosed where applicable. Marketplace listings, evaluations, and editorial materials are governed by our published standards and policies.