Run your models anywhere — datacenter, cloud, or edge. AI workloads are hungry, sensitive, and increasingly everywhere. nutanix.ms gives them a single, consistent platform on your terms.
AI puts contradictory demands on infrastructure — scale and sensitivity, speed and compliance, flexibility and control. Traditional approaches fail all of them.
Regulated data cannot leave approved locations. Public cloud forces sensitive workloads into compliance risk.
GPU instances at scale drain budgets fast. Training spikes and inference demands make costs impossible to forecast.
Inference that must happen in milliseconds can't wait for a round trip to a distant datacenter or cloud region.
Pure on-premises infrastructure can't flex when AI demand spikes, leaving teams stranded at capacity limits.
nutanix.ms resolves the infrastructure squeeze with a single operating model that spans datacenter, cloud, and edge — without forcing a rebuild every time your workload moves.
Deploy hyperconverged nodes provisioned for demanding AI workloads in your datacenter or at the edge.
Run training and inference where data lives. No egress costs, no residency risk, no latency penalty.
Hold sensitive data on-prem while bursting to cloud for capacity spikes — same operating model throughout.
Automated scaling, self-healing recovery, and identity-integrated security managed from a single control plane.
Every capability designed for the unique demands of AI workloads — from GPU provisioning to edge inference.
Hyperconverged nodes provisioned for demanding AI workloads, delivering the raw compute power modern models require without infrastructure rework.
Grow storage and performance as your AI ambitions expand. No re-architecting required — add nodes, expand capacity, and keep the same operating model.
Hold sensitive and regulated data on-premises while bursting to cloud for training spikes or capacity surges — all without changing how you operate.
Deploy AI where decisions actually need to happen. Run inference at branch locations, factory floors, or remote sites without shipping data to a central cloud.
One place to manage hybrid AI workloads across every environment. Whether on-prem, cloud, or edge — visibility, control, and policy in a single pane of glass.
Identity and security integrated from the start — not bolted on. Self-healing scale, automated recovery, and built-in resilience reduce operational toil.
From regulated financial services to latency-sensitive manufacturing — explore how nutanix.ms maps to your environment.
Deploy hyperconverged GPU-ready nodes in your datacenter with automated provisioning and configuration.
Keep your proprietary training datasets on-premises — no data leaves your environment or jurisdiction.
When training demand exceeds local capacity, automatically burst to cloud resources without reconfiguring anything.
Return trained model artifacts to your environment and serve inference locally for performance and cost control.
Run inference workloads on local GPU nodes, eliminating round-trip latency to the cloud.
Serve model responses to internal applications and APIs with sub-10ms latency at the source.
Self-healing infrastructure scales inference capacity automatically as request volume fluctuates.
Full observability of model performance, resource utilization, and latency from a unified control plane.
Stand up lightweight hyperconverged nodes at branch offices, factories, or remote sites.
Distribute trained model artifacts to edge nodes from the central control plane securely and automatically.
AI decisions happen at the source — no connectivity required for inference, no data leaves the site.
Updates, policies, and monitoring all flow from the central plane while execution stays at the edge.
Configure which data categories must remain in specific geographic or network boundaries within the control plane.
All workloads are automatically routed to compliant infrastructure based on data classification and residency rules.
Every data movement, model execution, and access event is logged for regulatory audit and governance review.
Real-time compliance monitoring ensures workloads never drift outside approved boundaries.
From financial compliance to real-time manufacturing AI — nutanix.ms adapts to the exact demands of your sector.
Run fraud detection, risk modeling, and customer intelligence on-premises where data must stay. Burst training jobs to cloud while keeping inference inside approved jurisdictions.
Deploy quality inspection, predictive maintenance, and operational AI at the edge. Sub-millisecond decisions without cloud dependency. Keep production running even offline.
Run diagnostic models and clinical decision support on patient data that cannot leave the facility. Meet HIPAA, HL7, and regional health data standards without sacrificing capability.
Government and defense workloads that require data to remain within national boundaries, on approved hardware, under direct operational control — not in a shared cloud.
nutanix.ms integrates natively with the tools, clouds, and platforms your teams already use.
Public cloud alone locks you into one provider's pricing, constrains data residency, and can't run inference at the edge where latency matters. nutanix.ms gives you a single operating model that spans your datacenter, any cloud, and edge locations — so you choose where workloads run based on compliance, latency, and cost, not infrastructure limitations.
Cloud burst is managed through the same unified control plane your team already uses for on-premises workloads. There's no separate cloud console, no retraining required. You set capacity thresholds and policy rules; nutanix.ms handles the bursting automatically while maintaining your operational posture.
nutanix.ms supports GDPR, HIPAA, SOC 2, FedRAMP-aligned deployments, and regional data sovereignty requirements. Data residency zones are configured at the platform level, and all routing respects those boundaries automatically — with immutable audit logs capturing every movement for regulatory review.
nutanix.ms runs on a broad range of certified hyperconverged nodes from leading hardware partners, including configurations optimized for GPU workloads. Edge deployments support ruggedized form factors for harsh environments. Your infrastructure team works with standard enterprise hardware procurement channels.
The unified control plane abstracts the underlying cloud and hardware differences. Whether workloads are running on-prem, bursting to AWS, deploying on Azure, or executing at an edge node — you see a single operational view. Policy, scaling, security, and monitoring are consistent everywhere.
Initial production deployments typically go live within days, not months. The hyperconverged architecture is designed for rapid provisioning — hardware arrives pre-validated, and the control plane is configured through guided automation. Most teams reach full operational capability in their first sprint.
Training and serving models should not lock you into one cloud or strand you in one datacenter. See how nutanix.ms resolves the AI infrastructure squeeze for your team.