An independent infrastructure for measuring and governing generative AI systems
NeoMundi Recherche is developing an independent infrastructure dedicated to measuring the real-world behavior of generative artificial intelligence systems.
Its mission is to make AI stability, variation, drift, and operating regimes observable, providing a measurement foundation that can support monitoring, auditing, and governance.
Generative systems already influence decisions, services, knowledge, and organizations. Yet their behavior in production remains largely invisible and may vary across models, providers, time periods, and usage contexts.
→ Explore the reference corpus on AI governance metrology.
→ View the AI Observatory publications
Scientific & Advisory Committee
NeoMundi Recherche brings together complementary profiles from research, education, auditing, law, and AI governance.
Their role is to help challenge methods, protocols, hypotheses, and published results, strengthening the scientific, technical, and institutional rigor of the program.
The Committee is not intended to operationally manage the Observatory. Its role is to provide an external, critical, and methodological perspective: challenging assumptions, identifying blind spots, examining reproducibility, and maintaining a strong standard of auditability.
Members
Thomas Hormaza Dow — Founder of the Business Physics AI Lab, Professor of Business With AI at Champlain College, and co-author of the REACT Framework – Cadre RÉAGI, focused on developing judgment in the use of AI in higher education.
Joël Ignasse — Science journalist for La Recherche. Author of Sur les traces du Nouveau T.rex (Eyrolles, 2025).
Cédric Chatelain — Quality consultant and IRCA-certified auditor specializing in auditing, validation, and ISO standards. Based in Bern, Switzerland.
James Aull — Founder of ASRO™, an independent witness and governed-state evidence layer for AI systems. Based in Twin Lake, Michigan, United States.
Inès Ramoul — GDPR & AI Act lawyer specializing in digital law, data protection, and AI governance. Legal and compliance contributor to the NeoMundi AI Observatory. Based in Lyon, France.
→ Discover the Observatory contributors
A measurement-based approach
NeoMundi does not simply observe generative systems: we measure them over time.
We develop and publish reproducible protocols, aggregated data, and open analyses to build a common foundation for traceability and comparison.
This approach is grounded in behavioral metrology for AI systems: establishing measurement references, tracking their evolution, characterizing variability, and detecting observable changes in operating regimes under real-world conditions.
An independent infrastructure
Independence is reflected in the choice of infrastructure, the progressive openness of methods, and the involvement of external perspectives.
The Observatory relies in particular on Infomaniak’s Swiss cloud, an infrastructure partner enabling contributors, researchers, and data scientists to work in a secure, privacy-first environment independent from the major providers whose models are being observed.
This separation helps preserve NeoMundi’s ability to produce measurements independently from the systems being measured.
Public and longitudinal observations
The Observatory’s work is progressively published in several forms:
- comparative public mappings of generative AI systems;
- regular stability and variation barometers;
- longitudinal analyses tracking the evolution of the same system over time;
- specialized studies by application domain;
- technical publications, datasets, and open methodologies.
NeoMundi Recherche does not seek to reduce AI systems to a ranking or a single score.
The objective is to build a common foundation for measurement, traceability, and public discussion, allowing the behavior of generative systems to be observed, compared, documented, and used as signals by governance infrastructures.