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Epsilon Health is the world’s first AI-native radiology practice, pairing world-class radiologists with purpose-built AI to interpret medical imaging faster and more consistently. As it scaled to thousands of patients a day, it needed a dedicated GPU cluster capable of training on native-resolution imaging data. Without the compute and iteration speed to match, its models couldn’t keep improving fast enough to keep up with demand.

Verda provided a dedicated NVIDIA Blackwell Ultra (B300) cluster with managed infrastructure and hands-on engineering support, letting Epsilon Health’s team focus entirely on model training.

Magnific was among the first to offer state-of-the-art media generation at scale. As its user base surged, it needed GPU infrastructure to absorb daily spikes while balancing latency, cost, and quality.

Verda provided a fully managed GPU fleet that scales elastically to absorb daily traffic spikes, paired with inference optimization that reduces generation latency and throughput cost without sacrificing model quality.

ExpressAI, ExpressVPN's new service, rests on a promise policy alone it cannot keep: prompts that no operator can access. That required LLM inference inside hardware-level isolation, without sacrificing performance or limiting scale.

Verda co-engineered confidential computing on NVIDIA's Blackwell architecture, extending hardware-attested isolation to multi-GPU configurations — bringing industry-first solution to production at scale.

While LLMs scale on text, robotics hit a physical data ceiling: teleoperation can't scale. 1X needed robots that learn by imagining and verifying actions, not copying task-specific demonstrations.

Beyond providing and managing GPU infrastructure, Verda co-engineered a multi-GPU inference engine to scale 1X's video world models — turning a breakthrough into a fast, production-ready policy running on NEO.