AI Compute Capacity
ANTARES owns and operates the GPU infrastructure, providing managed compute capacity under customer-specific service terms.
Sovereign AI capacity. Deployed where it is needed.
ANTARES builds and operates modular GPU infrastructure for enterprise AI inference.
OVERVIEW
Two ways to access one AI infrastructure platform.
GPU Colocation
Customers bring their own GPU hardware. ANTARES provides the facility, power, cooling and connectivity required to operate it.
MARKET CONTEXT
AI deployment is a physical infrastructure problem.
Production AI depends on available power, cooling, GPUs, network connectivity and an operating environment that meets uptime, security and data-location requirements.
For enterprises, compute capacity is not interchangeable. The relevant questions are where it is located, when it can be commissioned, which hardware it supports and whether it can expand with demand. ANTARES addresses that layer directly by integrating the physical systems required to run AI workloads continuously.
WeeksShort cycle
Models & applications
Fast-moving, iterating weekly
YearsLong cycle
Physical infrastructure
Slow-moving, the foundation
MARKET AVAILABILITY
Vacancy is tightening across major global data-centre markets.
Average vacancy by region
WORKLOAD FOCUS
Built for production inference.
Production inference serves live, variable demand. Capacity must be planned around response time, availability, data location and operating cost, not only GPU performance.
ANTARES focuses on sustained inference environments designed for continuous service and measured expansion.
TRAINING
Build the model
Existing data
Training run
Trained model
INFERENCE
Use the model
New input
Trained model
Live response
INFRASTRUCTURE
A modular system, configured for each site.
ANTARES integrates enclosure, protected power, liquid cooling, networking and GPU systems into a modular deployment. At power-secured, permit-ready sites, the target is 12 to 18 months to operation; conventional greenfield programs can require five to seven years when power access and site development are included.
LOCATIONS
Swiss-based, European in focus.
ANTARES evaluates locations across European markets according to customer proximity, available power, connectivity, site readiness and jurisdiction. Capacity is not tied to one fixed mega-campus.
Location is one part of the answer.
Sovereign infrastructure gives customers defined choices over where systems operate, who can access them and which operating model applies. Network design, identity controls, application architecture and contractual responsibilities determine how those choices work in practice.
Proximity, separation and phased expansion.
For production inference, regional placement can shorten network paths to users and support defined workload-location requirements. Separate locations limit shared physical failure, while modular capacity can be added where power, permits and demand are available. Continuity across sites still requires explicit replication, routing and recovery design.
Spain
Italy
Slovenia
Croatia
Germany
Austria
Liechtenstein
Switzerland
DELIVERY
One accountable path. From site to operations.
ANTARES coordinates site readiness, system design, equipment integration and the operating model. Suppliers are qualified for each project against compatibility, availability, support and lifecycle requirements.
Site readiness
Power, permits, connectivity and site constraints are validated before the equipment configuration is fixed.
Parallel delivery
Site preparation and factory fabrication can proceed in parallel. Timing still depends on power, permits, equipment supply and commissioning scope.
Integrated systems
Electrical, thermal, compute and network architecture are specified together for the site and intended workload.
Operations
Telemetry, access control, maintenance, spares and incident response are defined before commissioning.
TECHNOLOGY AND DELIVERY ECOSYSTEM
PROJECT MODELS
How deployments may be financed and owned.
The appropriate structure depends on the project, its assets, customer arrangements, financing requirements and participating parties. The examples below explain the available concepts at a high level.
Equity
Equity participation in a defined infrastructure project. Outcomes depend on customer contracts, utilization, operating costs, financing and residual asset value.
- Participation in project cash flows
- Exposure to project assets and liabilities
- Governance defined in the investment documents
Debt
A project-level debt instrument. Coupon, maturity, security package, covenants and any conversion rights are defined for each issuance.
- Security subject to the issuance documents
- Defined coupon and maturity
- Conversion only where expressly offered
GPU ownership
Direct title to identified GPU hardware, hosted and operated under contract by ANTARES. Returns depend on utilization, pricing, operating costs and the equipment's useful life.
- Title to identified physical hardware
- Income linked to contracted utilization
- Technology and residual-value risk remains
DISCLAIMER. This document is a strategic and marketing overview prepared by ANTARES consult finance real estate AG for discussion purposes only. It does not constitute an offer or solicitation to buy securities, does not constitute a prospectus, and is not investment, legal or tax advice. Figures and structures described are illustrative planning assumptions and are subject to change; no return is guaranteed and actual results may differ materially. ANTARES consult finance real estate AG is not a bank, does not accept public deposits, and is not subject to FINMA supervision. Prospective investors should seek independent professional advice before making any decision.
ANTARES designs and integrates modular GPU infrastructure, including power distribution, liquid cooling, compute, networking and the operating environment. Depending on the project, ANTARES either hosts customer-owned GPUs or provides AI compute capacity.
Modular deployment allows capacity to be added in defined increments as power and customer demand become available. It supports phased growth across separate locations while keeping each deployment sized to its site and intended workload.
Revenue comes from two main models: hosting customer-owned GPU hardware and providing AI compute capacity. Pricing and service scope are developed for each project based on the hardware, power, location, workload and operating requirements.
The starting points are customer demand, available power, delivery schedule, equipment selection, investment cost, operating budget and downside assumptions. These show whether the project logic remains understandable when utilization, pricing or timing change.
The most important variables are utilization, rental pricing, electricity cost, operating expenses, deployment timing and the useful life of the GPUs. The calculator makes these assumptions visible so different scenarios can be compared consistently.
Hardware is selected for the intended workload, customer demand, support position and expected economics. The modular design allows systems to be added or replaced in stages instead of requiring the entire infrastructure platform to change at once.
Assessment begins with the selected GPU, expected workload, metered electricity consumption, cooling design and total facility load. Energy source, renewable generation, battery storage and grid services are considered at the level of the individual location.
The most useful information is specific and project-based: location, available power, technical design, selected hardware, delivery stage, customer use case, investment assumptions and operating data. This makes it easier to distinguish the current project position from future plans.
CONTACT
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