Catalogue of Tools & Metrics for Trustworthy AI

These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.

EuConform



EuConform is an open-source toolkit and open specification for producing technical evidence of compliance with the EU AI Act. Organisations covered by the AI Act, such as providers and deployers of AI systems, will need technical evidence including inventories, documentation, logs and proof of human oversight. This evidence is often kept in PDFs, screenshots or proprietary dashboards, which are hard to check, update or share across tools. EuConform addresses this by producing structured, machine-readable evidence. It runs offline, so data stays within the organisation. It is designed to be usable by start-ups, public bodies and smaller firms, not only large companies. It provides technical guidance only and does not constitute legal advice.

A command-line tool scans an AI system's code and produces four types of evidence file. An AI bill of materials lists the models, runtimes and other components. A report identifies compliance signals, gaps and open questions across seven compliance areas. A CI (continuous integration) file lets development pipelines warn or fail when evidence gaps pass set thresholds. A bundle packages these files with cryptographic hashes, so reviewers can verify they have not been altered.

Users can then review the evidence in a web app. The app also offers an interactive risk classification based on Article 5 (prohibited practices), Article 6 and Annex III (high-risk systems). A bias testing module measures stereotypical bias in language models using the CrowS-Pairs method, including about 100 test pairs adapted for German. EuConform is written in TypeScript and dual-licensed under MIT and EUPL-1.2.

Auto-discovered on 2026-07-11 by OECD Catalogue Automation

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Disclaimer: The tools and metrics featured herein are solely those of the originating authors and are not vetted or endorsed by the OECD or its member countries. The Organisation cannot be held responsible for possible issues resulting from the posting of links to third parties' tools and metrics on this catalogue. More on the methodology can be found at https://oecd.ai/catalogue/faq.