Claw Computer builds and deploys on-prem GPU systems for teams running OpenClaw, local AI agents, computer vision, and factory automation workloads that cannot risk sending critical operations into the cloud.
Designed for environments where uptime, local data handling, and safety matter more than generic cloud convenience.
Hardware positioned for local agent systems, private orchestration, and heavier local model execution.
Predictable infrastructure for organizations tired of unpredictable cloud bills and external dependencies.
Start with a node. Expand to racks, clusters, and larger private AI deployments as demand grows.
The world is moving toward more AI in physical environments, but many important workloads should not depend on remote cloud infrastructure. Factories, industrial teams, and local AI operators need safe, controlled compute where the work actually happens.
OpenClaw makes the story more concrete. Buyers immediately understand that Claw is not abstract “AI hardware.” It is infrastructure for running real local agent workloads, private automation, and model-driven systems on hardware you control.
The strongest wedge on this page is not “servers.” It is the claim that factory-related AI and automation should be deployed as safely, locally, and predictably as possible. That is much stronger than generic AI hardware marketing.
The products are still important, but now they support the bigger story: safer local AI deployment for OpenClaw, factory automation, and private AI infrastructure growth.
For smaller local AI deployments, OpenClaw testing, and first production systems.
For serious OpenClaw, local model serving, factory AI, and production-grade private deployments.
For organizations building larger private AI clusters for factories, labs, and industrial deployments.
| Spec | Red | Green Blackwell | Rack Scale |
|---|---|---|---|
| FP16 throughput | 778 TFLOPS | 3,086 TFLOPS | 9,258 TFLOPS |
| GPU configuration | 4× 9070XT | 4× RTX PRO 6000 | 12× RTX 6000 Pro |
| GPU memory | 64 GB | 384 GB | 1,152 GB |
| CPU | 32-core EPYC | 32-core Genoa | Multi-node Genoa |
| System RAM | 128 GB | 192 GB | 768 GB |
| Storage | 2 TB NVMe | 4 TB RAID + 1 TB boot | 16 TB RAID |
| Networking | 2× 1GbE | 2× 10GbE | 400GbE fabric |
| Best fit | First local deployment | Production node | Integrated cluster |
This should feel simple to a buyer: tell us what you need to run, where you need to run it, and how safe the deployment needs to be. Claw recommends the system, the configuration, and the path to expansion.
OpenClaw, computer vision, factory AI, local agents, or private model serving.
Office, lab, factory, machine area, industrial site, or rack deployment target.
Hardware, memory, networking, deployment scope, and lead time matched to the use case.
Start with a system or rack and grow into larger private AI infrastructure over time.
This section removes hesitation and makes the sales conversation easier.
Factories, industrial operators, AI startups, private labs, and organizations running OpenClaw or local AI systems that need more control than public cloud gives them.
Because that is a stronger and more specific wedge than generic AI hardware. Factory automation and local operational AI naturally favor safer, more controlled on-prem deployment.
Because it grounds the story in a real local AI use case. It helps buyers understand the machine is built for actual agent and automation workloads, not vague future promises.
No. Claw starts with single systems but is designed around growth into racks and larger clusters as workloads expand.
The fastest path to a sale is simple: describe the workload, the environment, and how critical safe local deployment is. We will recommend the right system and the next step.