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TIERS AX

AI & GPU Systems

High-performance GPU workstations and servers for local AI, accelerated analytics, computer vision, authorized password recovery, and specialized compute workloads.

Build-to-order engineering Burn-in & validation Security-focused options Documented configuration
Need a system, not a parts list? TIERS Group starts with the workload, operating environment, data volume, security requirements, deployment model, and support needs.
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TIERS AX family

Graphics processing unit systems sized around the model, data, and workload

Artificial intelligence (AI) and accelerated compute systems can become expensive quickly if graphics memory, Peripheral Component Interconnect Express (PCIe) lanes, power, thermals, storage throughput, and model requirements are not designed together. TIERS Group starts with the intended workload and then engineers the platform.

Local AI / LLM

Single- or multi-GPU systems sized for artificial intelligence and large language model (LLM) memory, inference, experimentation, private local workflows, and expansion requirements.

Computer Vision

GPU, memory, storage, and input/output (I/O) designed around image/video analysis, dataset size, and compatible acceleration frameworks.

Accelerated Analytics

High-throughput local compute for compatible analytical, scientific, forensic, and data-processing workloads.

Password Recovery

GPU-dense configurations for lawful, authorized password-recovery workloads using client-approved software and data.

Private Compute

On-premises or controlled local systems where data residency, offline operation, or reduced cloud exposure is a business requirement.

Thermal & Power Engineering

Chassis, power supply unit (PSU), cooling, circuit requirements, noise, and sustained-load behavior are considered before the GPU count is finalized.

Configure the requirement

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Give us enough information to engineer the right starting point. Do not submit passwords, software license keys, evidence, export-controlled technical data, protected client data, facility security details, or other sensitive information through this public form.

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System requirement
Workload

Examples: forensic suites, VM count, AI model class, expected evidence volume, storage growth, networking, GPU use. Do not include license keys or sensitive case information.

Keep requirements high level. A TIERS engineer can collect sensitive configuration detail later through an approved channel if needed.

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