FlexAI on Neoclouds and AI Factory

Install the FlexAI platform on your GPUs for a Vertical Solution on your own datacenter, sovereign cloud or private cloud.

Standing up an “AI factory” on your own hardware or a neo-cloud looks attractive for cost and control, but it’s hard to operate. Teams juggle multiple runtimes and drivers, fight for capacity, and get locked into a single vendor.

Hyperscalers are driving customers to a vertical solution and GPUaaS from a neocloud provider might not entice users to switch. Utilization stays low, bursts cause outages, and every new workload means more manual setup.

The result: infrastructure bottlenecks, wasted compute, and unexpected downtime.

FlexAI delivers a workload-first AI Compute platform for neo-clouds, Cloud Service Providers and private AI clouds

FlexAI installs on your GPUs (datacenter, sovereign cloud, private cloud) and gives you a vertical, intent-driven control plane. We help you control capex, maximize users and increase the returns on your spend

Maximize Infrastructure

Multi-tenancy and Autoscaling support in control plane supports Elastic GPU resource provisioning
Fixed Slices (MIG) and Time-Slicing support in Hardware
Fair-share policies to prevent noisy-neighbor slowdown
Managed checkpoints keep long jobs progressing based on health and metrics
Drive to 100% utilization across all nodes with no wasted capacity

Diversify Compute

Multi-architecture support (NVIDIA, AMD, and other accelerators) so you’re never locked in
Match workload to the best hardware class for price/performance
Simple policy rules to prefer or exclude vendors, regions, or SKUs

Automate Operations

Service Provider admin view for Tenant Provisioning and Onboarding
Developer-friendly UI/CLI with Jupyter SDK support;
Tenant IT-friendly admin view with role-based access (RBAC) and quota management
Built-in scheduling, retries, and placement logic—no custom scripts
Unified observability with dashboards on cost, performance, and health metrics

Support Any Workload

One platform for pretraining, fine-tuning, inference, and RAG solutions
Provide containers, Baremetal services as well as managed AI services side-by-side without reconfiguring clusters
Consistent APIs so teams can move from prototype to production without refactors

Future-Proof AI Deployment

Scale across regions and burst to public cloud when queues build
Hybrid patterns out of the box: on-prem steady state, cloud for peaks
Policy-as-code for residency and routing to meet compliance requirements

Expand Private AI

Keep data and models under your control with sovereign and on-prem options
Enterprise-grade security, auditing, and isolation for regulated workloads
Maintain autonomy while retaining cross-cloud freedom

Benefits

No infrastructure bottlenecks: Launch and scale workloads without queueing or manual setup.
No wasted compute: Sustain >90% GPU utilization with automatic right-sizing and dynamic scaling.
No downtime: Checkpoints, smart placement, and burst-to-hybrid patterns keep services available.
Lower cost, longer runway: Up to 50% lower compute spend by eliminating idle capacity and picking the best-fit hardware.
Faster time to value: Jobs can launch in under 60 seconds with zero DevOps overhead.
Launch and scale wSovereignty and control: Own your data, choose your region, and avoid single-vendor lock-in.orkloads without queueing or manual setup.

One platform. Any cloud. Any hardware. Anywhere.

Get Started with $100 Credit