Performance
Engineer compute, storage, fabric, power and cooling as one workload-led system.
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DESIGN, IP + R&D MADE IN ITALY
Design the system.
Advance the technology.
IUNOVRA combines hardware and thermal design, software development and AI research to improve how infrastructure is built and operated. Simulation, prototyping and testing turn promising ideas into validated designs and repeatable delivery methods.
DESIGN · VALIDATE · PROTECT · INDUSTRIALISE
THE STRATEGIC INTENT
Not a catalogue of components.
A reusable infrastructure architecture.
The most valuable layer sits at the interfaces: workload-to-system design, thermal and power control, composability, orchestration, validation and the operating data that improves the next deployment.
Efficiency
Optimise liquid cooling, heat rejection, power conversion and operational control together.
Scalability
Reuse validated modules from retrofit and rack scale through POD and distributed infrastructure.
Defensibility
Protect designs, software, know-how and validated delivery methods where the advantage compounds.
SOVEREIGN BY DESIGN. OPEN BY ARCHITECTURE.
Technology ownership
where it matters most.
IUNOVRA develops the engineering and software layer.
Our focus is system architecture, thermal and deployment design, InfraMind software, operating logic and continuous R&D. Project agreements define ownership, licensing and rights to use each deliverable. Selected compute, cooling, power, storage and networking technologies are integrated through supported interfaces, with compatibility validated for each engagement.
For customers: control of infrastructure, data, permissions and operating policy—with hardware choice across supported integrations.
ENGINEERING + SOFTWARE DOMAINS
From chip-level thermal control
to full infrastructure orchestration.
These are engineering and research domains, not a list of universally available features. Composable GPU pools, dynamic allocation and advanced optimisation require the relevant interfaces, prototypes and deployment-specific validation.
Advanced liquid cooling
- Direct-to-chip liquid cooling design
- Cooling distribution and facility integration
- Retrofit cooling for existing servers
- Rack-side heat exchange and free-cooling integration
AI-ready system architecture
- High-density liquid-cooled compute nodes and racks
- Research into disaggregated GPU pools
- Composable NVMe storage pools
- Modular architecture from rack to AI POD
Efficient, governed operation
- High-efficiency power delivery and protection
- Unified allocation and policy control
- InfraMind digital twin and orchestration
- Energy, capacity and reliability optimisation
COMPOSABLE ACCELERATOR R&D
GPU capacity designed to move
beyond fixed server boundaries.
IUNOVRA is developing an architecture that separates accelerator capacity from fixed server configurations. The aim is to let supported hosts access a governed GPU pool—helping operators adapt capacity, improve utilisation and avoid unnecessary server expansion.
Separate capacity
Explore accelerator resources as a composable infrastructure layer rather than a permanently fixed server component.
Assign with control
Provide supported hosts with governed access through validated hardware and software interfaces.
Integrate the platform
Connect future accelerator pools with AI POD infrastructure, data services and InfraMind operational intelligence.
INTENDED WORKLOAD FIT
Throughput-oriented and parallel workloads
Research targets include inference, media processing, scientific workloads and other parallel compute patterns.
ENGINEERING BOUNDARY
Validated for the workload—not positioned as universal
Strongly coupled training workloads may require different interconnect architectures and are not assumed to fit this model.
Architecture, interoperability and operating behaviour remain subject to prototype testing and deployment-specific validation.
SOFTWARE IP
Make infrastructure composable,
intelligent and measurable.
Engineering and software development connect operational visibility to governed action. Each engagement distinguishes demonstrated functions, integrations requiring validation and development objectives. Predictive models, autonomous control and billing are separately scoped—not implied by a digital twin.
PHYSICAL INFRASTRUCTURE + DIGITAL CONTEXT
The asset and its operating context. Connected.
InfraMind connects resources, relationships and live state in one model, giving people and AI the context needed for governed action.
- Live state and resource relationships
- Shared context across connected systems
- Permission-aware decisions and actions
Coordinated control
Connect supported resource controls, capacity context, policy and access. Dynamic allocation and composable resources are validated for the selected architecture.
InfraMind
An operational digital twin connects supported resources and their state. Monitoring and approved workflows provide the foundation; predictive analysis and optimisation require suitable data, models and deployment-specific validation.
Service economics
Develop usage and energy measurement to support service economics. Pricing, SLA reporting and billing integrations require a separately agreed scope.
THE R&D SYSTEM
Every deployment should make
the next one better.
Operating constraints guide designs, simulations, prototypes and validation. The programme below describes our engineering approach; it is not a claim that every research domain is a completed or certified product.
FROM DESIGN TO VALIDATION
Make engineering assumptions testable.
Thermal designs become prototypes with measurable requirements. Validation connects simulation to performance, serviceability and real operating constraints.
- Model thermal and power trade-offs
- Prototype and test against a baseline
- Turn evidence into reusable design rules
Observe
Capture workload, thermal, power and operational constraints.
Design + simulate
Model the architecture and test trade-offs before deployment.
Prototype + validate
Prove performance, reliability, efficiency and maintainability.
Protect
Secure relevant designs, software, know-how and industrial rights.
Industrialise
Convert learning into reference architectures and repeatable modules.
TANGIBLE ENGINEERING OUTPUTS
From a design question
to an evidence-backed deliverable.
Each engagement selects its outputs and acceptance criteria. These are possible deliverables—not a claim that every item is already available.
System designs
Architecture, interfaces, component selection and operating limits for the workload and site.
Prototypes and test evidence
Agreed simulations, prototypes, test plans and results against explicit performance and reliability requirements.
Software and integration specifications
Supported functions, APIs, data flows, permissions and deployment requirements.
Reusable delivery knowledge
Validated design rules, documentation and handover material, with ownership and usage rights defined.
WHAT YOU RECEIVE
A clear scope before delivery.
- Deliverable
- An agreed engineering output: design, prototype, software integration or validation report.
- Site requirements
- Workload requirements, existing designs, access to test equipment and acceptance constraints.
- Integration scope
- IUNOVRA work packages, partner inputs, existing IP and new development boundaries.
- Acceptance criteria
- Defined test methods, success criteria and evidence required to advance the design.
- Support responsibilities
- Ownership, licensing, documentation, maintenance and the next industrialisation stage.
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.
COLLABORATE ON THE NEXT ARCHITECTURE
Turn a hard constraint
into reusable advantage.
Engage IUNOVRA on workload architecture, thermal and energy design, prototype validation, InfraMind integration or a joint R&D programme.