Thermal intensity
High-density accelerators need cooling matched to their heat load, including liquid cooling where required.
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02 / AI POD
Deploy around the workload.
Scale through modular design.
Deploy AI capacity where the workload needs it—from edge cabinets and containerised systems to high-density, multi-module data centres. AI POD brings compute, storage, networking, power and software into one engineered system, with cooling matched to the workload. Modular systems also form building blocks for distributed infrastructure.
ONE INTEGRATED SYSTEM / COMPUTE, DATA, POWER AND COOLING ENGINEERED TOGETHER
THE NEED
Capacity must fit the workload—and the location.
Available power, cooling, latency and data-location requirements determine where AI can run. A POD brings these decisions into one engineered system, instead of leaving the customer to reconcile separate equipment and facility projects.
Integration complexity
Compute, fabric, storage and facilities must perform as one validated system.
Location and control
Sensitive data and latency-critical applications can require computing close to the source, with explicit access and operating policies.
Scale uncertainty
The entry configuration must expand without forcing a complete redesign.
THE IUNOVRA RESPONSE
A modular platform with one accountable architecture.
IUNOVRA configures the POD around the workload and deployment environment, using interoperable building blocks and InfraMind as the operating intelligence layer.
WHAT YOU RECEIVE
A clear scope before delivery.
- Deliverable
- A configured system design, bill of materials and commissioning scope.
- Site requirements
- Available power, heat rejection, connectivity, space and resilience requirements.
- Integration scope
- Included equipment, customer-provided power and site services, software and external interfaces.
- Acceptance criteria
- Workload performance, thermal behaviour, protection and resilience tests for the configuration.
- Support responsibilities
- Equipment warranties, software licences, support coverage and ownership of site operations.
Scope and availability
Technical descriptions include reference designs and configuration options. The proposal separates demonstrated functions, integrations to validate and development work; only the agreed scope is included. Performance and service commitments follow the acceptance criteria.
DELIVERY MODEL
From assessment to operation.
Assess & design
Agree the workload, site readiness, interfaces and acceptance criteria.
Factory integrate
Assemble the selected configuration and document integrated system tests.
Commission
Connect site services and verify performance, safety and operating readiness.
Hand over & support
Provide operating documentation, responsibilities and agreed lifecycle support.
Validate & expand
Use deployment evidence to replicate the design across additional sites.
TECHNICAL DEPTH
Inside an AI POD.
Explore the functional layers, then see how the POD connects to site power, cooling and networks.
INSIDE AN AI POD
Nine connected layers.
One engineered system.
Explore what each layer does and where the POD connects to the customer's infrastructure.
From hardware to operations.
Labels identify functions, not exact equipment positions. Heat rejection may sit outside the cabinet; InfraMind connects the system as a software layer.
01Enclosure & racksThe physical foundation
POD configuration
Cabinet, rack or modular enclosure with mounting, cable routing and service access. Environmental protection, physical access and internal layout are selected for the installation—not assumed to be identical at every scale.
02Compute & AI accelerationThe workload engine
POD configuration
CPU servers and GPU or other accelerator systems matched to inference, training, fine-tuning, analytics or HPC. Processor choice, memory and topology are balanced against the application and power envelope.
03StorageKeep the workload supplied with data
POD configuration
Local or pooled storage sized for throughput, capacity, checkpointing and protection. NVMe/SSD tiers and expansion enclosures are selected where required; encryption and data-integrity controls follow the agreed design.
04NetworkingConnect compute, data and users
POD + site interface
Top-of-rack switching, Ethernet or InfiniBand where appropriate, fibre uplinks and a management network. Fabric bandwidth, segmentation and connections to customer networks are defined together.
05Power distributionDeliver power safely and visibly
POD + site interface
Protection, intelligent power distribution units and metering connect the POD to the available electrical supply. UPS and generator capacity may be site-provided or separately scoped; they are not automatically included in every POD.
06Liquid-cooling systemRemove processor heat
Configuration-dependent
Where required, compatible cold plates, manifolds, connections, CDUs and pumps form the cooling architecture. Flow, temperature and leak monitoring are specified alongside residual air cooling and maintenance access.
07Heat-rejection systemMove heat beyond the POD
Site or dedicated equipment
A suitable facility cooling connection, dry cooler, heat exchanger or chiller arrangement completes the thermal design. Equipment location and capacity depend on climate, operating temperatures and site constraints.
08Monitoring, controls & securityProtect the operating environment
POD + site interface
Temperature, flow, pressure and leak sensing provide operational visibility. Humidity, smoke, access control, video and fire systems are selected as needed and coordinated with the site's safety and security provisions.
09InfraMind software layerConnect infrastructure to operations
Agreed software scope
InfraMind brings telemetry and infrastructure context together for visibility, alerts and governed operations. Orchestration, optimisation, fleet management and integrations are defined by the deployment scope and supported interfaces—not assumed to be available in every configuration.
Explore InfraMind →THE POD + THE SITE
One architecture.
Configured for the workload.
Integrated with the site.
Standardised building blocks. Site-specific engineering. The same design principles connect an edge cabinet or a modular facility to the infrastructure around it.
AI PODCompute · Storage · Network
Power · Cooling · Software
Power · Cooling · Software
Configured as one coordinated system
Power & resilience
Utility feeds, UPS and batteries; generators where required.
Cooling & heat rejection
Site cooling or dedicated CDUs, pumps, dry coolers or chillers.
Fibre & network
External connections, customer networks and redundant routes as specified.
Safety & security
Fire protection, physical security, access and maintenance provisions.
DEPLOYMENT OPTIONS
- Compact edge
- Multi-rack AI
- High-density compute
- Modular AI facility
Clear interfaces. Explicit responsibilities. Supporting equipment may be site-provided or delivered as dedicated modules—not automatically included in every POD. Capacity, resilience, site conditions and the operating model determine the final scope, commissioning tests and acceptance criteria.
VALUE + DECISION MODEL
From an edge cabinet to a modular AI facility.
One product family, configured at the scale the workload needs. Start with a bounded validation where appropriate, then expand after performance, site readiness and operating ownership are established.
Compact edge cabinet
- Local inference and analytics
- Cybersecurity, caching or telecom functions
- Existing site services where suitable
Bring computing closer to users, industrial equipment and data sources when latency or locality matters.
Multi-rack AI POD
- Balanced compute, fabric and storage
- Video analytics and industrial AI
- Shared or multi-workload environments
Increase capacity through an integrated rack group, with isolation and service levels defined for the intended users.
High-density configuration
- GPU clusters for demanding AI workloads
- Cooling matched to rack power
- Validated electrical and thermal interfaces
Engineer the compute and cooling system together for training, fine-tuning or other intensive workloads.
Prefabricated modular facility
- Modular compute capacity
- Dedicated power and cooling as required
- Repeatable expansion interfaces
Package larger capacity into a modular facility architecture. Grid connection, site works and resilience remain explicit design requirements.
HOW THE CASE IS VALIDATED
Cost per usable workload
Evaluate delivered throughput, utilisation and availability—not hardware price in isolation.
Time to productive capacity
Plan assessment, factory integration, logistics and site commissioning separately. On-site installation time is not the full order-to-operation lead time.
Lifecycle economics
Model energy, cooling, support, refresh, software and expansion over the operating life.
Scale gate
Expand after performance, reliability, demand and operating ownership are demonstrated.
Configuration, density, deployment time and economics vary by accelerator generation, workload, facility interface, resilience level and supply availability. All figures require a customer-specific design and bill of materials.
CUSTOMER BENEFITS
Why choose an AI POD?
Deploy where power is viable
Size capacity around suitable electrical and cooling infrastructure. Modular deployment can widen location choices, but does not remove grid or permitting requirements.
Bring compute closer
Run local inference and data-intensive applications near users, equipment and datasets when latency or data movement makes central processing less suitable.
Expand with demand
Replicate validated configurations as workloads grow. Evaluate each addition against utilisation, service levels and full lifecycle costs.
Design for sovereign operations
Combine deployment location with access policies, data governance and defined support dependencies. Supported InfraMind integrations provide a common operating view across the estate.
A distributed estate is not automatically one high-performance GPU cluster. Tightly coupled training needs a validated low-latency, high-bandwidth fabric; local inference and independent jobs have different requirements. Every site still needs suitable power, connectivity, cooling and support.
How this connects to the wider IUNOVRA platform
WHY IT IS STRATEGIC
More than a project.
A platform advantage.
Independent engineering partner
IUNOVRA combines its own design and software capabilities with selected partner technologies. Differentiation comes from engineering compute, storage, cooling and power around the workload—with coordinated interfaces and acceptance criteria, not a claim to manufacture every component.
Brownfield and partner integration
PODs can connect to suitable existing facilities, with mechanical, electrical and network upgrades scoped explicitly. Open interfaces support customer and partner technology choices, subject to compatibility validation.
Industrialisation, not just installation
The delivery plan identifies engineering, assembly and testing responsibilities, partner facilities and support arrangements. Location and readiness are confirmed for the selected configuration.
Distributed capacity. Coordinated operations.
Replicate validated PODs where site power, workload proximity and data policies support deployment. InfraMind connects supported sites through a common operational model, while each retains its own capacity, access and resilience boundaries.
LET’S DISCUSS YOUR PROJECT