Engineering compute at the desk or laboratory
Hyperion workstations
Configured-to-order systems for CAD, CAM, simulation, scientific computing, AI development, analytics and technical software development.
Plan this platformAxiotech Hyperion systems
Engineering compute designed from workload, deployment and lifecycle constraints.
Configured workstations, rack servers and clusters for simulation, AI and technical computing—with component compatibility, operations, destination and formal quotation treated as engineering gates.
Choose by operating model
Three platform routes
The quotation review may reshape an indicative configuration where software, power, cooling, serviceability or compliance evidence requires it.
Production-class shared compute
Hyperion rack servers
Rack systems for shared simulation, private AI, data services, build/test infrastructure and production engineering workloads.
Plan this platformScale-out systems with explicit operations
Hyperion compute and AI clusters
Multi-node platforms for distributed simulation, shared AI training/inference, high-throughput jobs and organisation-scale technical computing.
Plan this platformFrom estimate to supplied system
Configuration is the start of quotation—not checkout
HPC and AI systems remain subject to technical, commercial and compliance review.
- 1Describe workloadSoftware, datasets/models, concurrency, current evidence and target constraint
- 2Build indicative configurationCPU, memory, GPU, storage, networking, power, rack and expansion
- 3Engineering reviewCompatibility, bottlenecks, environment, support, destination and export screen
- 4Formal quotationConfirmed scope, availability, price, validity, terms and delivery assumptions
Plan before selecting components
Workload and architecture guidance
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Hyperion X-Series models
Representative starting points with simplified public pricing and configuration routes.
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Application planning
Start with solver, model, dataset, concurrency, latency and operating needs.
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Platform architecture guide
How CPU, memory, GPU, storage and fabric constraints interact.
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