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.

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Orthrus

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Orthrus

Orthrus offers comprehensive features for AI system identification, risk classification, and compliance management. 
Key features include AI system identification (AI Scanner), and risk classification (In. 
It provides guidance on implementing best practices and addressing regulatory requirements.

 

Feature 1: AI System Identification
AI Scanner leverages advanced detection algorithms to automatically identify and catalog all AI systems operating within an organization. This ensures comprehensive visibility, preventing any AI application from going untracked, even in complex IT environments. By automating system identification, it enhances accuracy, reduces reliance on manual audits, and supports compliance with the EU AI Act’s requirements for AI system oversight.

 

Feature 2: Inventory & Model Monitoring
AI Scanner provides continuous monitoring and classification of identified AI systems, offering a structured inventory aligned with regulatory frameworks. It assesses risk levels—minimal, high, or unacceptable—enabling organizations to prioritize compliance efforts effectively. With real-time tracking and intuitive risk insights, this feature supports proactive governance, transparency, and strategic decision-making.

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Tags:

  • ai compliance
  • regulation compliance

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Use Cases

European AI Scanner: Ensuring Compliance with the EU Artificial Intelligence Act

European AI Scanner: Ensuring Compliance with the EU Artificial Intelligence Act

Background: In an era of rapidly advancing artificial intelligence (AI) technologies, ensuring their responsible and ethical use has become a pressing concern. The European Union (EU) recognizes the significance of regulating AI systems to safeguard ...
Aug 14, 2023

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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.