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

LLM Survey for responsible and transparent and safe AI covering international compliance regulations and data/ model evaluations

Ethical Problem Solving (EPS) is a framework to promote the development of safe and ethical artificial intelligence. EPS is divided into an evaluation stage (performed via Algorithmic Impact Assessment tools) and a recommendation stage (the WHY-SHOULD-HOW method).

The Algorithmic Transparency Certification for Artificial Intelligence Systems, by Adigital, is a robust framework for ensuring AI systems operate with paramount transparency, explainability and accountability. Grounded in universal ethical principles, it assesses AI systems on various critical factors, preparing organizations for evolving regulations like the EU AI Act, enhancing societal trust, and fostering competitive market advantage. This certification embodies a dynamic tool for continuous improvement, driving AI innovation with a solid foundation of responsibility and ethical consideration.

Our software equips data scientists and AI engineers with powerful tools to help them create robust and explainable AI systems in conformity with ISO standards. Trust Saimple to help you build the foundation for reliable AI.

A software-based EU AI Act compliance solution for your clients and AI value chain actors

Trustworthy AI (Measuing trust)

Enterprise platform for governance, risk and compliance in AI. Regulatory compliance with global laws intersecting with AI.

GRACE is an AI governance platform that offers a central registry for all AI models, tools, and workflows for risk mitigation, compliance, and collaboration across AI teams and projects. It provides real-time compliance, transparency, and trust while promoting AI innovation. The platform works across all major cloud vendors and offers out-of-the-box frameworks for complying with EU AI Act, AI standards, data regulations, and AI frameworks.

A scalable and systematic solution empowering enterprise to adopt and scale AI with confidence and enhance business performance.

A fully independent and impartial audit to ensure compliance with the bias audit requirements for New York City Local Law 144 and upcoming regulations.

A bespoke AI risk audit solution tailor-made to identify your enterprise project’s AI risks, comprising deep technical, quantitative analysis.

A set of guides to help enterprises mitigate some of the most common AI risks, presenting step-by-step solutions to protect against technical risks.

The Holistic AI library is an open-source tool to assess and improve the trustworthiness of AI systems. The library offers a set of techniques to easily measure and mitigate Bias across a variety of tasks.

Zupervise is a unified risk transparency platform for AI governance.

Naaia, the first AIMS on the market in Europe, is the governance and management solution for AI systems without compromising ethics or compliance (AI ACT)

A standardised label / short datasheet that can be attached to AI products to show their charactaristics with regards to principles like transparency, accountability, privacy, fairness and reliability.

Model cards are the tool for transparent AI documentation. Model cards are essential for discoverability, reproducibility, and sharing. You can find a model card as the README.md file in any model repo. Under the hood, model cards are simple Markdown files with additional metadata.

The use of Artificial Intelligence (AI) is one of the most significant technological contributions that will permeate the life of western societies in the coming years, providing significant benefits, but also highlighting risks that need to be assessed and minimized. A reality as disruptive as AI requires that its technology and that the products and […]

The IEEE CertifAIEd™ Program offers a risk-based framework supported by a suite of AI ethical criteria that can be contextualized to fit organizations’ needs– helping them to deliver a more trustworthy experience for their users. IEEE CertifAIEd Ontological Specifications for Ethical Privacy, Algorithmic Bias, Transparency, and Accountability are an introduction to our AI Ethics criteria. We […]