FluidStack builds and operates large-scale compute infrastructure for AI, including gigawatt-class data centers and GPU clusters used for training and inference. The company designs its own power, cooling and data center systems, onshores manufacturing and deploys solar generation to supply the power its clusters need. Rather than a self-serve cloud console, FluidStack works with AI labs and enterprises to provision large reserved clusters, with orchestration tooling for the ML frameworks and schedulers those teams already use.
FluidStack builds and operates large-scale compute infrastructure for AI, including gigawatt-class data centers and GPU clusters used for training and inference. The company designs its own power, cooling and data center systems, onshores manufacturing and deploys solar generation to supply the power its clusters need. Rather than a self-serve cloud console, FluidStack works with AI labs and enterprises to provision large reserved clusters, with orchestration tooling for the ML frameworks and schedulers those teams already use.
Datacenter-scale compute built in-house
FluidStack designs and builds large AI data centers, including high-density campuses with significant per-site power capacity, rather than reselling capacity from other clouds.
GPU clusters for training and inference
Clusters are architected for large-scale model training and inference, with high-bandwidth interconnect and orchestration suitable for distributed workloads.
Power and cooling engineered together
The company develops off-grid solar and recirculating closed-loop cooling, treating power and water efficiency as core engineering problems.
Managed operations and reliability
Smart hands, cluster provisioning and operations support let research teams focus on models while FluidStack runs the physical and orchestration layers.
优势与优点
+Purpose-built AI infrastructure rather than generic cloud resale
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