AI Ethics for Fairness is a software application that supports the detection, evaluation and mitigation of bias in AI models by analysing datasets, training models and applying fairness processing techniques.

FACTS Grounding is a comprehensive benchmark for evaluating the ability of LLMs to generate responses that are not only factually accurate with respect to given inputs, but also sufficiently detailed to provide satisfactory answers to user queries.

AuditNLG is an open-source toolkit for auditing the trustworthiness of generative AI text. It evaluates outputs across three key dimensions: factualness (consistency with knowledge), safety (harmful or biased content), and constraint adherence (compliance with instructions). The tool aggregates multiple state-of-the-art methods and provides scores, explanations, and improved text suggestions via self-refinement prompts. It supports both API-based and local models, enabling flexible integration into evaluation pipelines and governance frameworks.

Judgment Assurance is a decision-governance discipline that reframes human judgment as a governed institutional asset. It provides a structured framework and practical instruments, including the Underwriting Questionnaire (JA-UQ) and Maturity Model (JAMM-PS), to ensure that consequential AI-mediated decisions are reconstructible and defensible. By defining minimum governance controls for human oversight, it closes the "accountability gap," allowing institutions to define, record, own, and guard the reasoning behind consequential AI-supported outcomes.

The Approved Intelligence Platform (AIP) provides modular, scenario-based testing workflows to evaluate mission-critical AI systems in defence, public safety, and critical civil use cases. It delivers a comprehensive, end-to-end testing environment based on a proprietary AI trust ontology with measurable AI Solutions Quality Indicators (ASQI) for the testing, evaluation, validation and verification of software solutions with different AI modalities.

The AI Governance Playbook from the Council on AI Governance helps organizations align people, processes and tools to achieve responsible AI outcomes.

An artificial intelligence (AI) impact assessment tool to provide organisations a method to assess AI systems for compliance with Canadian human rights law. The purpose of this human rights AI impact assessment is to assist developers and administrators of AI systems to identify, assess, minimise or avoid discrimination and uphold human rights obligations throughout the lifecycle of an AI system.

An open-source Python library designed for developers to calculate fairness metrics and assess bias in machine learning models. This library provides a comprehensive set of tools to ensure transparency, accountability, and ethical AI development.

The Python Risk Identification Tool for generative AI (PyRIT) is an open access automation framework to empower security professionals and machine learning engineers to proactively find risks in their generative AI systems.

The deck of 50 Trustworthy AI Cards™ correspond to 50 most relevant concepts under the 5 categories of: Data, AI, Generative AI, Governance, and Society. The Cards are used to create awareness and literacy on opportunities and risks about AI, and how to govern these technologies.

Warden AI provides independent, tech-led AI bias auditing, designed for both HR Tech platforms and enterprises deploying AI solutions in HR. As the adoption of AI in recruitment and HR processes grows, concerns around fairness have intensified. With the advent of regulations such as NYC Local Law 144 and the EU AI Act, organisations are under increasing pressure to demonstrate compliance and fairness.

FairNow is an AI governance software tool that simplifies and centralises AI risk management at scale. To build and maintain trust with customers, organisations must conduct thorough risk assessments on their AI models, ensuring compliance, fairness, and security. Risk assessments also ensure organisations know where to prioritise their AI governance efforts, beginning with high-risk models and use cases.

AI Security Platform for GenAI and Conversational AI applications. Probe enables security officers and developers identify, mitigate, and monitor AI system security.

The Algorithm Charter for Aotearoa New Zealand is a set of voluntary commitments developed by Stats NZ in 2020 to increase public confidence and visibility around the use of algorithms within Aotearoa New Zealand’s public sector. In 2023, Stats NZ commissioned Simply Privacy to develop the Algorithm Impact Assessment Toolkit (AIA Toolkit) to help government agencies meet the Charter commitments. The AIA Toolkit is designed to facilitate informed decision-making about the benefits and risks of government use of algorithms.

The purpose of the present document is to provide information on different types of AI mechanisms that can be used for cognitive networking and decision making in modern system design, including natural language processing.

This document addresses bias in relation to AI systems, especially with regards to AI-aided decision-making.

Privacy compliance platform, based on AI/Blockchain, which helps global companies to keep compliant with the data protection requirements.

Enzai’s EU AI Act Compliance Framework makes achieving compliance with the world’s first comprehensive AI governance legislation as easy as possible. The framework breaks hundreds of pages of regulations down into easy-to-follow steps allowing teams to enable organisations to seamlessly and confidently assess the compliance of their AI Systems with the Act and complete the requisite conformity assessments.

NayaOne is a Sandbox-as-a-Service provider to tier 1 financial services institutions, world-leading regulators, and governments. This sandbox is designed to address key concerns in AI deployment by providing a single environment where AI can be evaluated and procured while also enabling collaboration and access to world-leading tools.

Developed by the AI Verify Foundation, Moonshot is one of the first tools to bring Benchmarking and Red-Teaming together to help AI developers, compliance teams and AI system owners evaluate LLMs and LLM applications.