Build-to-suit
High-density AI capacity, built around your workload.
Customers define what they need to run. Psionics owns the GPUs and servers, operates the data center, and configures the capacity around those requirements.
Whether the workload is an AI software factory, inference service, or agentic system, we bring site, power, cooling, hardware, network, commissioning, and operations into one delivery plan.
What the capacity is built for
The workload sets the infrastructure requirements.
The same delivery model adapts to different customers because the capacity, hardware, network, and operating model begin with what needs to run.
AI software factories
Dense compute environments for building, testing, training, and deploying AI systems over time.
- Capacity planned around the development path
- Compute, storage, and network designed together
- Room to add the next phase
Inference workloads
Dedicated capacity configured around the throughput, latency, availability, and geographic needs of the service.
- Capacity matched to expected demand
- Network and service requirements set upfront
- Reliable day-to-day operation
Agentic systems
Infrastructure designed for concurrent workloads, changing demand, and the supporting services that keep agents running.
- Compute sized around task volume and concurrency
- Controls for data, access, and customer use
- A clear path to more capacity
What Psionics owns and operates
The data center and GPU fleet stay under one operating team.
The data center
Psionics operates the power, cooling, network, physical infrastructure, and site services.
- Facility design and delivery
- Site operations and maintenance
- Monitoring and incident response
The GPU and server fleet
Psionics owns the compute infrastructure and configures it to meet the customer requirement.
- GPU, server, storage, and network equipment
- Hardware refresh and capacity planning
- Integration, testing, and commissioning
Delivery and expansion
Psionics coordinates the work needed to add capacity while keeping the existing service running.
- Suppliers and manufacturing relationships
- Phased deployment and acceptance testing
- Capacity reporting and future expansion
Start with the requirements