We work with visionary organizations and believe in the ability of human beings to drive conscious, responsible innovation to change the world for the better.
A three-level educational program designed to meet the specific needs of our clients, preparing individuals to use innovative technologies in compliance with legal requirements.
A flexible, recorded training program divided into short modules that enables the widespread and consistent dissemination of the technical, ethical, and legal implications of AI.
In-person session (approximately 5 hours) for multidisciplinary groups, consisting of an initial segment of lecture-style training and interactive discussion of use cases, followed by a guided workshop to apply what has been learned in a practical setting.
A modular program tailored to specific stakeholder groups, organized by role (new hires, Board of Directors, AI Task Force) or by topic based on the results of our AI Readiness Test.
We develop strategic and adaptive governance models to guide sustainable and reliable AI projects.
Develop a strategic vision for AI, grounded in the organization’s goals and values, to prioritize use cases and guide complex, hybrid (human-AI) decision-making processes, ensuring alignment with what matters most to you.
Set up the AI organizational chart, including the governance model and the distribution of roles and responsibilities within the organization.
Definition of the AI Governance Framework, including the documents required for regulatory compliance (code of conduct, policies, guidelines), and joint definition of ethical and regulatory KPIs (percentage of trained personnel, growth in the innovation rate, number of compliance documents, number of low- and high-risk systems).
We incorporate contextual qualitative and quantitative assessments designed to anticipate and guide the impacts of AI in terms of ethics, sustainability, human rights, and compliance.
Semi-automated ethical assessment of the impacts and risks of an AI project to quickly identify the most vulnerable areas and plan mitigation strategies.
Quantitative testing using queries designed to evaluate the model against various ethical parameters (consistency, correctness, fairness, competence, manipulation, and reliability).
A new social metric for measuring the (positive) social and environmental impact of AI through an economic framework. A tool for planning, measuring, and reporting the value of AI use cases.
