Connected engineering, fewer handoffs
Facility, GPU, runtime and application decisions affect one another. We bring them into one engineering conversation so trade-offs surface before procurement and deployment.
END-TO-END EXPERTISE FOR HIGH-PERFORMANCE COMPUTING.
Why ElioVP
ElioVP is a Belgian AI engineering company that helps organizations build and run AI on infrastructure they control.
Baseline first. Connect the layers. Measure the delivered result.
What makes ElioVP different
Connected decisions, measurable results and control over how you run AI.
Performance you can examine
In the original matched Qwen3.8 test on one Radeon AI PRO R9700, Paiton on regular vLLM delivered 57% higher throughput than Radiance + DFlash2 at eight concurrent requests. The result belongs to that 188-request, 8K-context benchmark, not to every model or deployment.
Control where it matters to you
Managed cloud services reduce the infrastructure your team has to operate. When data location or operational control calls for an on-prem alternative, we help design it; neither route is automatically cheaper or more secure.
PROOF POINTS
Experience at scale, with scope made clear
250,000+GPUs deployed, as recorded in AMD's 2025 ElioVP profile
5,000+AMD EPYC CPUs supplied, cumulative ElioVP figure
~€500MCumulative revenue since founding, company-reported
Companyweb reports €215.45 million turnover for 2024. The near-€500 million cumulative figure is reported by ElioVP; the public summary does not display turnover for every earlier year. View public annual figures
EXTERNAL VALIDATION
Recognition you can verify
Enterprise infrastructure decisions require more than broad claims. ElioVP’s work is publicly documented through official technology-company channels.
Official article
ElioVP featured by AMD
AMD’s official article introduces Paiton by ElioVP and discusses ElioVP’s work on performance tooling, AI optimization and AMD platforms.
In a video published by AMD Data Center, ElioVP CEO and founder Elio Van Puyvelde explains how the team uses ROCm to optimize workloads across AMD Instinct GPU generations.
The AMD Tech Talk episode “Thinking Outside the Box” explores ElioVP’s origins and end-to-end infrastructure work.
Customer success story PDF
Published Supermicro customer success story
Supermicro’s official success story documents ElioVP’s work with server, storage and GPU infrastructure for demanding workloads.
This provides externally published evidence of ElioVP’s practical infrastructure and performance-engineering experience.
Official marketplace listing
Public NVIDIA marketplace listing
ElioVP appears in NVIDIA’s official enterprise partner marketplace.
This gives prospective customers a direct external source through which they can verify ElioVP’s presence in the NVIDIA partner ecosystem.
Infrastructure applied in the real world
Selected examples of how ElioVP applies compute, facility and optimization expertise across demanding infrastructure environments.
HPC DEPLOYMENT
Boosting Performance with HPC Solutions
ElioVP helped align server infrastructure, deployment requirements and workload performance for a demanding HPC environment.
INFRASTRUCTURE MODERNIZATION
Enhancing Infrastructure
ElioVP integrated high-performance compute systems into an existing enterprise environment, improving capacity and platform readiness.
MODFLEX MODULAR DATA CENTERS
Sustainable ModFlex Modular Data Centers
ElioVP developed a purpose-built ModFlex modular data center concept around site conditions, power, cooling and future expansion requirements, using building-based modular facilities, engineered steel-frame modules and custom modular buildings.
SUPERCOMPUTING
AMD-Powered Supercomputer
ElioVP delivered and optimized a large AMD-based compute environment for cloud and high-performance workloads.
The team behind ElioVP
ENGINEERING CREDENTIALS
Tier Standards expertise within our team
Our engineering team includes an Uptime Institute Accredited Tier Specialist. That expertise informs decisions around resilience, availability and operations, but does not imply a project is Uptime Institute certified unless certification is separately scoped and achieved.
This strengthens our ability to identify infrastructure risks and align data center concepts with the required level of operational resilience.
How ElioVP works
Agree the baseline, responsibilities and evidence of success before building.
- 01
Start with a direct conversation
Contact us through the website or by phone and describe the task, constraints and decision you need to make. You will speak with the team that can assess the relevant engineering scope.
- 02
Scope and measure
We review representative workloads, available infrastructure, data boundaries and operational requirements. The proposal defines deliverables, commercial terms, communication cadence and the measurements used to judge the result.
- 03
Build, validate and hand over
The relevant engineers deliver the agreed system or workflow and test it against the defined baseline. Handover and any ongoing support are scoped explicitly, including the customer’s operational responsibilities.
Response targets, turnaround times, meeting channels and support coverage are agreed for each engagement; we do not publish a universal SLA or fixed delivery time.
Better infrastructure economics, not just faster hardware.
ElioVP looks at the full cost of a workload: what you buy, how efficiently it runs, and what it costs to operate and grow.
The goal is to remove waste before it becomes locked into the architecture.
Buy what the workload needs
Workload and capacity planning help avoid over-provisioning, mismatched components, and expensive redesigns.
Get more from the hardware you own
In our MiniMax H3 test, one R9700 saved a 15-second video with stereo sound 16.7% sooner. Warm, complete-request timing with the same settings.
See the measured resultReduce lifecycle friction
One end-to-end technical partner connects sourcing, deployment, operations, and expansion, surfacing cost trade-offs earlier and reducing unnecessary handoffs.
More useful work from every system and watt
Efficiency claims should begin with an agreed baseline. ElioVP models capacity, utilization, useful throughput, power, cooling, and operating requirements around the actual workload.
The objective is practical: avoid unnecessary capacity, improve useful output from deployed systems, and make energy and lifecycle trade-offs visible before they are locked into the architecture.
Cost reduction is customer- and workload-specific. ElioVP agrees the baseline, scope, and measurement method before making a project-specific business case. No universal saving is implied.
What ElioVP does
From facilities and GPU systems to the applications your team uses.
Modular data centers
ModFlex facilities are designed around your site, power, cooling and resilience requirements, with room for operations and expansion.
AI infrastructure and GPU clusters
We plan and deliver GPU servers, storage, networking and cooling sized for your models and concurrent users. Capacity decisions are tested before procurement.
Sovereign and on-prem AI
Run selected models and applications on hardware you control, from a workstation to a shared server. We plan data flows, access, licences and support alongside the hardware.
Paiton inference optimization
Paiton improves inference performance for documented models and hardware configurations. Published benchmarks and community packages make the setup, results and limitations available for review.
AIDesk business workspace
AIDesk brings documents, team chat, customer context, tasks and AI assistance into one workspace, without replacing your existing email service.
Applied AI and team enablement
We build agents and computer-vision workflows around business tasks, with human review where needed. Ready AI Go trains teams in safe, practical AI use.
Who uses ElioVP
For teams making practical AI and infrastructure decisions.
- IT and AI teams deploying private assistants, document search and coding tools.
- Enterprises and public-sector teams planning sovereign AI and data controls.
- AI platform and HPC teams specifying GPU systems and clusters.
- Operators, developers and investors planning modular data-center capacity.
- Business teams improving information access, coordination and repetitive workflows.
Key facts
A concise reference for the public facts we can state. Project-specific commercial details and customer names are shared only where approved.
Frequently asked questions
What does ElioVP do?
We design and optimize the systems that make demanding AI and compute workloads useful in practice, from GPU infrastructure and modular facilities to model serving and business applications. The engagement starts with your workload and operating requirements.
Can ElioVP help us run AI on our own premises?
Yes. We can scope a workstation or server, select and test a suitable model, and plan its data flows, access and support. On-prem hardware alone does not guarantee security or compliance; those controls must be designed and operated.
Do we need a large GPU cluster?
Not necessarily. Many internal assistants and document workflows can start with a smaller system, while larger workloads may need multi-GPU capacity. We size against representative tasks, memory needs, concurrent users and response targets.
How are Paiton performance claims measured?
We publish benchmark conditions, baselines and limitations for specific models and hardware. A result such as the original 57% Qwen3.8 throughput gain is a measured comparison under its stated test configuration, not a general guarantee.
Can we see customer references?
Recognition from AMD, Supermicro and NVIDIA is publicly verifiable. Selected customer project material can be discussed privately with qualified organizations when customer agreements permit it.
What will a project cost and how long will it take?
Both depend on the use case, equipment, site and delivery responsibilities. We define pricing, contract terms, response expectations and milestones in the project proposal rather than publishing a universal promise.
Bring us the baseline and the result you need.
We will connect the relevant infrastructure, performance, sovereignty, and workflow decisions into a focused first assessment.
Discuss your use case