We're building the future of
GPU infrastructure

We've spent years building and scaling AI/ML infrastructure services at large tech companies. We've seen the same problem everywhere: teams demanding more GPU capacity when others let their capacity sit idle.

The problem lay in two forms: first, we lacked visibility across our organizations to identify the actual usage of GPU capacity, and second we needed to build the ability to share idle capacity across teams to allow them to burst onto other teams idle GPUs.

We built these platforms in the past and now we're building the best version yet using our combined learnings working with hundreds of AI/ML teams.

We joined Y Combinator (W26 batch) to accelerate our mission of helping AI/ML teams run more experiments, ship faster, and get the most out of the GPU investments.