Artificial Intelligence Tools for Green Hydrogen Production and Quality Assurance

IDENER.AI offers a full range of artificial intelligence capabilities to optimise production, reduce operational costs and improve product quality. Our core competences cover supervised and unsupervised machine learning for process monitoring, reinforcement learning for real‑time energy management, anomaly detection for predictive maintenance of fuel cell/electrolyser stacks, and computer vision for automatic inspection of hydrogen purity and equipment integrity. All these tools are deployed with a modular, scalable architecture that adapts to the existing infrastructure, allowing a smooth transition from TRL 6 to TRL 9.

Our team has proven experience in multiple European collaborative projects where we deployed AI‑based solutions in industrial environments, including chemical process optimisation, energy systems and advanced manufacturing. In particular, we have worked extensively with data from electrolysis and gas processing units, giving us a deep understanding of the operational constraints and data characteristics of hydrogen production. Moreover, we can support the project coordinators during proposal preparation, from defining the technical concept and selecting the appropriate methodology to writing the work plan, impact section, and budget justification.