AI training & inference
GPU-dense systems, rack-scale platforms and clusters sized for model development, fine-tuning, retrieval, inference and accelerated analytics.
Regional DevelopmentNetworks LLC
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AI infrastructure & enterprise computing
Compute engineered
Compute engineered
around the mission.
Vendor-neutral configuration and integration support for corporate AI, industrial computing, HPC, private cloud and modern data-center platforms.
Plan your infrastructure
Technology integration
From workload brief
From workload brief
to operational platform.
RDN translates business, engineering and AI objectives into an executable infrastructure plan. We align compute, acceleration, memory, storage, networking, power, cooling, security and lifecycle support before equipment is selected.
Consulting & configuration
One architecture.
One architecture.
Every critical layer.
Configurations are built around the application, data profile, service level, deployment environment and growth model—not around a single manufacturer catalogue.
Enterprise servers
High-availability compute for ERP, databases, virtualization, VDI, private cloud, containers and business-critical applications.
Storage & data platforms
High-throughput file, object and block architectures with data protection, tiering, governance and recovery requirements defined.
Network fabric
Low-latency Ethernet and accelerated interconnect design for east-west AI traffic, storage access, management and secure segmentation.
Industrial & edge AI
Rugged and compact systems for vision, automation, inspection, remote operations and low-latency inference near the source.
Facility readiness
Rack density, redundant power, cooling, liquid-cooling interfaces, physical layout and deployment sequencing coordinated with the data center.
Integrated system design
Performance is a system property.
Accelerators alone do not determine results. CPU topology, GPU memory, interconnect bandwidth, storage throughput, software compatibility, power and thermals must operate as one validated platform.
Representative Supermicro pathway. GPU-optimized servers or rack-scale systems can be configured with NVIDIA accelerators, AMD EPYC or Intel Xeon host processors, high-speed fabric, AI-ready storage, redundant power and air or liquid cooling. Final selection follows the workload, site conditions and regional availability.
Workload firstModels, users, data & SLA
Right-sizedCapacity, redundancy & growth
Deployment readyRack, power, cooling & network
DocumentedBOM, topology & acceptance plan
Application pathways
Built for the work.
Built for the work.
Ready to scale.
Each solution is scoped against measurable workload and operational requirements, with the freedom to compare complete OEM systems and best-of-breed component architectures.
Generative AI & private models
Secure platforms for model serving, retrieval-augmented generation, fine-tuning and internal AI applications.
HPC & accelerated analytics
Parallel compute, simulation, scientific workloads, rendering and high-volume analytics.
Private cloud & virtualization
Consolidated infrastructure for virtual machines, containers, VDI and critical business services.
Edge AI & computer vision
Low-latency inference for manufacturing, logistics, inspection, security and remote facilities.
AI-ready storage
High-bandwidth data pipelines, scalable namespaces, protection and tiering for active and retained datasets.
Data-center modernization
Capacity planning, density migration, resilient network and power design, and cooling-readiness coordination.
Engagement path
Clear decisions.
Clear decisions.
Controlled delivery.
The engagement can cover a focused system configuration or an end-to-end program—from workload discovery through supplier alignment, installation coordination and acceptance.
Discover
Define workloads, users, data, service levels, security and site constraints.
Architect
Model compute, storage, fabric, power, cooling and expansion requirements.
Compare
Evaluate validated OEM and component pathways against fit, lead time and lifecycle.
Deploy
Coordinate supply, staging, documentation, logistics, installation and commissioning.
Operate
Plan monitoring, spares, support, upgrades, capacity and refresh cycles.
Technology ecosystem
Leading AI and data-center platforms
Representative manufacturers and platform providers considered across accelerated compute, enterprise servers, networking, storage and private-cloud infrastructure.
NV
NVIDIADGX, accelerated compute & networking
SM
SupermicroGPU, rack-scale & enterprise systems
IBM
IBMPower, LinuxONE, storage & hybrid infrastructure
DELL
Dell TechnologiesPowerEdge, storage & AI infrastructure
HPE
HPEProLiant, Cray & private-cloud systems
LEN
LenovoThinkSystem, HPC & enterprise platforms
CSCO
CiscoUCS, switching & AI-ready infrastructure
FJ
FujitsuPRIMERGY, PRIMEHPC & enterprise compute
NEC
NECHPC, AI & enterprise systems
GB
GIGABYTEGPU, HPC & data-center servers
ASUS
ASUSAI, GPU & enterprise server platforms
QCT
QCTCloud, AI & rack-scale data-center systems
PS
Penguin SolutionsAI factories, HPC & cluster integration
INS
InspurAI, cloud & enterprise server systems
AMD
AMDEPYC processors & Instinct accelerators
INTC
IntelXeon, accelerators & data-center platforms
NTAP
NetAppEnterprise data & AI storage
PURE
Pure StorageAll-flash data platforms for AI
DDN
DDNAI & HPC data infrastructure
VAST
VAST DataAI data platform & scalable storage
WEKA
WEKAHigh-performance data platform for AI
NTNX
NutanixPrivate cloud & enterprise AI platform
VMW
VMware by BroadcomVirtualization & private-cloud infrastructure
RH
Red HatOpenShift AI & hybrid-cloud software
Manufacturer names and marks identify common technology ecosystems only. Their display does not imply that RDN is an authorized distributor, agent or partner. The list is representative rather than exhaustive; availability, support route, regional compliance and authorization are confirmed for each inquiry.
Qualified projects
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