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

Newton’s Tree’s Federated AI Monitoring Service (FAMOS) is a dashboard for real-time monitoring of healthcare AI products. The dashboard is designed to enable users to observe and monitor the quality of data that goes into the AI, changes to the outputs of the AI, and developments in how healthcare staff use the product.

Resaro offers independent, third-party assurance of mission-critical AI systems. It promotes responsible, safe and robust AI adoption for enterprises, through technical advisory and evaluation of AI systems against emerging regulatory requirements.

Defining quality measures for quantitatively evaluating system and software product quality in terms of characteristics and subcharacteristics defined in ISO/IEC 25010 and is intended to be used together with ISO/IEC 25010.

The document highlights quality objectives for organizations responsible for datasets. The document describes control of records during the lifecycle of datasets, including but not limited to data collection, annotation, transfer, utilization, storage, maintenance, updates, retirement, and other activities.

This document lists examples of and defines categories of use cases for machine learning in medicine for clinical practice.

This document gives the requirements, under which image recognition problems in medicine can be addressed using a Deep Learning image recognition system.

This standard identifies the core requirements and baseline for AI solutions in health care to be deemed as trustworthy.

This standard is aimed at establishing concepts and terminology for the performance and safety evaluation of artificial intelligence medical device, which covers basic technology, dataset, quality characteristics, quality evaluation and application scenario.

PRIDAR (Prioritization, Research, Innovation, Development, Analysis, and Review) A Risk Management Framework

A global communityof 500+ researchers from 57+ countries, with foundational free course in a Human Rights-based approach to AI development that explores concrete builds of systems centering human rights values. Community is further enriched by reading & discussion groups, and written community outputs.

Citrusx offers a multifaceted solution to connect all stakeholders in the company through an SDK, user-friendly UI, and automated reporting system.

This guidance addresses one type of generative AI, large multi-modal models (LMMs), which can accept one or more type of data input and generate diverse outputs that are not limited to the type of data fed into the algorithm.

Advice for policy-makers on how to plan, develop and implement federated learning systems to safely advance machine learning for health systems improvement.

Use Saidot to empower AI teams to do high-quality AI governance efficiently and with quality

Automate, simplify, and streamline your end-to-end AI risk management process.

Based on abstract interpretations, Saimple leverages state-of-the-art techniques described in ISO/IEC 24029 standards for the assessment and validation of AI model robustness

The Data Carbon Scorecard provides a rapid assessment of the environmental impact of your proposed data project enabling you to quickly gauge the CO2 implications of your data project and determine the ‘best’ course of action for the environment. Through answering just 9 questions, the scorecard provides you with a traffic light display of data CO2 hotspots and an overall Data CO2 Score for the whole project within minutes. The scorecard can be used by any individual, team, or organization.

QuantPi’s puts AI systems to the test. It is the cockpit of AI-first organizations to collaborate on – to efficiently and responsibly understand, enhance and steer their individual AI models as well as their complete AI landscape.

Aival provide independent quality assurance systems to evaluate and monitor AI in healthcare