Web application that allows organizations to assess their level of maturity in artificial intelligence governance and automatically generate a customized roadmap to meet national and international standards

This handbook provides guidance on ethical and legal responsibilities associated with the use of high-risk AI systems in the EU civil security domain, focusing on use cases in border control, policing, and immigration. The aims of the handbook are to provide a structured pathway for engaging and understanding deployer responsibilities as outlined in the AI Act, focusing on high-risk AI systems, and to help establish processes for the ethical use of AI solutions.

Lightweight AI safety auditing framework for red-teaming AI systems through adversarial probing. Supports multilingual testing across safety, healthcare, and RAG scenarios, and works with cloud APIs or fully local models.

The Google Responsible Generative AI Toolkit provides tools and guidance to design, build and evaluate open AI models responsibly.

Content Credentials provide tamper-evident metadata that gives you more information about how a piece of digital content was created and edited.

Eureka is a reusable and open evaluation framework for standardizing evaluations of large foundation models beyond single-score reporting and rankings.

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.

WasItAI is an image-checker designed to detect AI-generated photos.

The Resaro AI Solutions Quality Index (ASQI) provides a transparent, use-case-specific measure of AI quality — for applications such as customer chat services, object recognition, deepfake detection, or x-ray anomaly identification.

MISSION KI is developing a voluntary quality standard guideline for artificial intelligence (AI) that strengthens the reliability and trustworthiness of AI applications and systems. It sets a voluntary, evidence-based self-assessment framework for AI providers below the EU AI Act’s high-risk threshold. It defines six quality dimensions (data governance, non-discrimination, transparency, human oversight, reliability, AI-specific cybersecurity) and a stepwise procedure: describe the use case, analyse protection needs, rate requirements via a VCIO catalogue, document tests/evidence, validate findings, issue a report, and monitor validity.

MISSION KI's Compliance Monitor is a tool for monitoring compliance with legal frameworks to facilitate interoperability, data flows and benefit sharing.

As part of the MISSION KI project, the initiative has developed the innovative data set search engine (Daseen), which for the first time enables cross-source searches for data sets.

An open-source framework for large language model evaluations. Inspect can be used for a broad range of evaluations that measure coding, agentic tasks, reasoning, knowledge, behavior, and multi-modal understanding.

Elements of AI is a free online course, offered in Slovakia by AIslovakIA and Comenius University. Created by the University of Helsinki and Reaktor with EU support, it introduces the basics of artificial intelligence through six interactive modules.

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

CAST is an open framework for responsible AI design and engineering. It offers design heuristics and patterns, and RAI recommendations through generative features and online content.

ADMIT is a research tool within a broader methodological framework combining quantitative and qualitative strategies to identify, analyse, and mitigate social implications associated with automated decision-making systems while enhancing their potential benefits. It supports comprehensive assessments of sociotechnical impacts to inform responsible design, deployment, and governance of automation technologies.

Risk Atlas Nexus provides tooling to connect fragmented AI governance resources through a community-driven approach to curation of linkages between risks, datasets, benchmarks, and mitigations. It transforms abstract risk definitions into actionable AI governance workflows.

PolicyPilot is designed to assist users in creating and managing AI policies, streamlining AI governance with automated compliance monitoring and risk management.

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.