Software & Tools

Open-source toolset and visualization platform for AI explainability and fairness evaluation.

EXCALIBUR is building an open-source ecosystem that helps teams explain, audit, and communicate AI decisions in a human-friendly way. This page provides an overview of the project's software outputs, including libraries, interfaces, and resources that support transparency and fairness evaluation across the AI lifecycle. Tools will be released progressively as the project advances, with open-source components made available through dedicated releases and documentation.

Python Library

In Development

A comprehensive Python library that integrates the EXCALIBUR framework into real AI pipelines. Provides easy-to-use APIs for generating explanations and fairness reports.

Explainability Fairness LLM-powered

Web Platform

In Development

An intuitive web-based visualization platform that presents explanations and fairness reports in a transparent, user-friendly way. Supports human insight, interaction, and feedback.

Visualization Interactive User Feedback

GitHub Repository

Coming Soon

All code, tools, and platform components will be released as open-source on GitHub, enabling reuse and community contributions.

Open Source MIT License Community

Key Features

Model-agnostic explainability

Comprehensive fairness metrics

Human-readable explanations

Interactive visualizations

Privacy-preserving design

Easy integration with AI pipelines