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Train and deploy across a federated GPU/CPU fabric with security tiers (A-D), geo-controlled execution, and transparent pricing—built for speed without vendor lock-in
AI/ML on your terms. Not your clouds
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deploy with confidence
Control AI spend & compliance
Legacy clouds force you to choose between high performance, data sovereignty and cost, Our distributed cloud platform intelligently routes each workload to its ideal environment, so you don’t have to compromise.
Optimized compute subrates
Dynamically match jobs to the perfect infrastructure—from distributed GPUs for heavy training to edge CPUs for efficient inference.
Build-in data sovereignty
Automatically keep sensitive data within it’s required legal jurisdiction while running public workloads on the global edge for low latency.
built for ai delivery
Practical capabilities you can use today
Distributed training
Run data/model-parallel training across multiple GPUs and pools—under one control plane.
Geo-controlled inference
Serve models close to users on edge nodes while enforcing region tier constraints for compliance.
Tier-aware placement
Map jobs to security tiers: keep PHI/PII on higher-trust nodes; route public workloads to lower-cost tiers.
Portable by design
Use standard Kubernetes and declarative configs; avoid lock-in and retain multi-cloud optionality.
Energy-efficient edge
For non-sensitive inference and ETL, use NanoServers that use less energy than data centers.
Real-time cost visibility
See usage and spend by workload, cluster, and tier for predictable planning and faster iteration.
how teams ship smarter
From experiments to production—faster
Architect once, then place the right part of the pipeline on the right tier.
Foundation-model fine-tuning
Combine enterprise GPUs with overflow capacity under policy; track placement choices for audit and cost.
Latency-critical inference
Deploy endpoints on regional edge nodes; apply tier and residency constraints for governance.
Privacy-preserving training
Constrain training to specific jurisdictions and higher-trust tiers (A/B) for regulated datasets.
outcomes that matter
Ship faster—with control, compliance, and savings
DCP lets you align spend to sensitive while keeping your options open.
Spend 20%+ Less
Lower AI TCO via tier-aware placement and transparent pricing
Automate Compliance
Compliance-by-design with geo and tier controls (A-D)
Embrace ESG
Sustainable by default — edge NanoServers use up to 88% less energy
AS SEEN IN
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The Clear Choice for Intelligent Workloads
Why NexQloud outperforms AWS, Azure, and GCP for AI/ML
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NexQloud
AWS
Azure
GCP
Feature
Distributed GPU/CPU Fabric
Geo-Controlled Model Training
Tier-Aware (A-D) Job Placement
Save 50%+ on Non-Sensitive Workloads
Up to 88% Lower Energy Use for Inference
SUCCESS STORIES
Real results from organizations using NexQloud
Transform your cloud experience today
Accelerate business growth with tailored decentralized cloud solutions.
GET STARTED TODAY
You deserve a cloud that’s as smart as your data
With NexQloud DCP, your workloads are not just available and scalable — they route smarter, cost less, and run exactly on the tier they belong — not just in one legacy tier