Edge Data Centers
With over a decade of expertise, WAIYS powers next-generation performance with containerized infrastructure engineered for the most demanding AI and HPC workloads.
High Density – Low Latency
High Density
Delivering high performance computing power of up to 2 MW per container on a minimal installation footprint. No large premises required.
Low Latency
Data centers at the edge are ideal for powering AI applications that require low latency for real-time responsiveness.
Modular & Scalable
Adjustable concepts, available in different sizes, multiple performance tiers, and customizable configurations.
Turnkey Solution
Our containers come with complete equipment from computing and cooling system to safety & security features. No lengthy installation periods.
Modular Container Designs
Standard Class (40 ft)
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Fits 12–18 server racks (19″)
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Up to 2 MW computing power
Compact Class (20 ft)
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Fits 3–8 server racks (19″)
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Up to 1 MW computing power
Multi-Container Facility
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Various scalable layouts
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Multiple MW solution
Green Computing Power
Highest Energy Efficiency
Our containers deliver the lowest PUE on the market, combining ultra-efficient closed-loop liquid cooling with a compact installation footprint.
Reusing Excess Energy
By placing edge data centers directly at energy production sites, we turn excess energy – including flared gas – into revenue. This maximizes resource utilization and actively cuts emissions.
Waste Heat
We turn waste heat into a valuable resource, with outlet temperatures of up to 80°C ready to feed into district heating networks and other heat grids.
Boosting Renewable Energy
With edge data centers providing instant off-take for renewable energy, producers get the financial boost they need to kick-start and grow critical sustainability projects.
Software-Based Energy Optimization
Orchestration software optimizes distributed data centers by balancing loads between sites. This ensures that computing jobs run at all times in the most energy- and/or cost-effective way. The software solution evaluates and selects the most efficient location for running a job based on specific metrics, such as energy availability, heat demand, power pricing, and latency.
