GPU
Specialized hardware accelerator for parallel computations, widely used to train and run large-scale AI models efficiently.
Graphics Processing Units (GPUs) excel at matrix and tensor operations fundamental to deep learning. They dramatically reduce training and inference times but consume significant power and require specialized provisioning. Governance around GPU usage includes cost monitoring, job-scheduling policies, fair-share quotas, and retiring obsolete GPU generations to optimize performance-per-watt.
A research lab provisions a dedicated GPU cluster for AI experiments. They enforce time quotas per user, automatically decommission models running beyond limits, and track GPU utilization metrics to justify upgrades to more energy-efficient GPU architectures.
We help you find answers
What problem does Enzai solve?
Enzai provides enterprise-grade infrastructure to manage AI risk and compliance. It creates a centralized system of record where AI systems, models, datasets, and governance decisions are documented, assessed, and auditable.
Who is Enzai built for?
How is Enzai different from other governance tools?
Can we start if we have no existing AI governance process?
Does AI governance slow down innovation?
How does Enzai stay aligned with evolving AI regulations?
Research, insights, and updates
Empower your organization to adopt, govern, and monitor AI with enterprise-grade confidence. Built for regulated organizations operating at scale.