Advancing computer vision requires high-quality data and massive computing power. Training models on real-world datasets is slow, expensive, and vulnerable to edge-case failures. Synthetic data changes the equation.

Synetic.ai is pioneering a new approach, building physics-accurate simulation environments that generate photorealistic and perfectly annotated datasets. These adaptive simulations enable models to perform reliably in the real world across various industries, including defense, robotics, agriculture, healthcare, and manufacturing.

But to create billions of accurate light interactions and material behaviors, Synetic.ai needed fast, scalable GPU infrastructure. Traditional cloud providers introduced cost and latency barriers that slowed progress.

Vultr helps Synetic.ai remove those constraints.

With NVIDIA HGX B200 Bare Metal GPUs on Vultr, Synetic.ai can deploy and scale AI training environments globally, accelerate model development timelines, and maintain cost-efficient redundancy without operational friction.

That performance advantage is translating into real business impact. Synetic.ai has improved model generalization by more than 30%, cut rendering costs by over 40%, and tripled simulation capacity in just six months. The company is now winning major enterprise contracts and bringing AI-powered systems to market faster.

The physical world doesn’t limit the future of computer vision. It's a built-in simulation, powered by GPUs designed for the most demanding workloads.

Read the full customer story to see how Synetic.ai and Vultr are redefining what’s possible for vision-driven automation.