COMPUTE
AI compute. From cloud to data center.
Cloud capacity, private hardware and complete AI infrastructure, designed around the workload.
Cloud · Workstations · GPU Servers · AI Infrastructure
01 / CLOUD
Cloud
Access GPU compute without owning the infrastructure.
Inference · Training · Fine-tuning · Burst workloadsDedicated / SharedScalable capacityPrivate environments available
02 / AI WORKSTATIONS
AI Workstations
Dedicated local AI compute for developers, teams and specialized workloads.
Local inference · Development · Vision · Private AI
03 / PRIVATE AI SERVERS
Private AI Servers
Production AI infrastructure deployed inside your environment.
AI Employees · RAG · Inference · Model serving · Fine-tuningDeployment planningMemory and storage architectureNetwork, power and cooling design
04 / AI INFRASTRUCTURE
AI Infrastructure
From multi-server clusters to complete AI data-center projects.
RACK / CLUSTERMulti-node GPU infrastructure.
DATA CENTERComplete infrastructure architecture and deployment.
Compute · Network · Storage · Power · Cooling
05 / SIZING
Built around the workload.
We size the architecture before selecting the hardware.
MODELSWhat needs to run.
CONCURRENCYHow many workloads run simultaneously.
DATAWhere it lives and how quickly it moves.
LATENCYHow fast the system needs to respond.
PRIVACYCloud, private or isolated.
GROWTHWhat the infrastructure needs to support tomorrow.
06 / OPERATIONS
More than the hardware.
ARCHITECTURECompute, memory, storage, networking and workload sizing.
DEPLOYMENTCloud, on-premise, colocation and hybrid environments.
OPTIMIZATIONModel serving, quantization, batching, caching and GPU utilization.
OPERATIONSMonitoring, scaling and infrastructure lifecycle.
COMPUTE WITH MINDZY
What do you need to run?
From a single workstation to complete AI infrastructure.