
Dr. Sami Kama
Founder & CEO- 17 years at CERN
- Inventor, TensorFlow-TensorRT Integration (NVIDIA)
- Inventor and Architect, AWS SageMaker
- Inventor and Architect, AWS SageMaker HyperPod
- Creator, SageMaker Profiler (world’s first distributed AI profiler)
training · inference · agents
You keep control of your infrastructure, policies, and data.
Nucleaton™ manages your GPU cluster operations and schedules compute for training, inference and agents.
Run multi-node training and production inference on the same cluster.
Automatically isolate faulty nodes using the most advanced real-time telemetry. Reduce job failures and wasted compute hours.
Reallocate compute between training and inference to reduce GPU idle time.
“C-Gen.AI dynamically allocates idle compute to inference workloads, so AI resources are continuously utilized rather than sitting idle.”
Dr. Sami KamaFounder & CEO, C-Gen.AIThe cost of idle GPUs
<50%
GPU capacity is used on many AI clusters between training runs.
You still pay for the idle capacity.
GPU utilization over 24 hours, from 03:00. Before Nucleaton™: before working hours (03:00 to 09:00) inference uses 40% of the cluster and 60% of GPUs sit idle; in working hours (09:00 to 13:00) inference rises to 80% and 20% still sit idle. With Nucleaton™: for the rest of working hours (13:00 to 18:00) inference takes 80% and training the idle 20%; after hours (18:00 to 03:00) inference eases back to 40% and training takes the other 60%. With Nucleaton™ the cluster stays close to 100% busy.
Save seed capital on infrastructure engineering. Launch AI models faster.
Turn idle cluster compute into revenue with multi-tenant AI-as-a-Service.
Run secure, on-premises AI with built-in audit logs and cost attribution.
We’ve designed, built and run some of the largest AI training and inference systems in production.


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Stop managing infrastructure and start scaling.
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