GPU-optimized
AI data centers.
Facility systems, GPU-ready architecture, cloud connectivity, and implementation services for enterprise AI infrastructure.
Facility and IT systems
for enterprise AI.
Structured cabling, cooling, compute, storage, networking, security, and observability need to work together before AI infrastructure is production-ready.
Structured Cabling Systems
Fiber and copper backbone design, rack-level patching, labeling, and test-ready pathways for GPU data halls.
Cooling Systems
High-density cooling architecture for AI racks, including airflow planning, liquid-ready zones, and operational monitoring.
IT Systems
Compute, storage, networking, observability, and security systems delivered as an integrated AI infrastructure stack.
The physical layer
behind AI systems.
Premium AI infrastructure depends on disciplined facility, rack, network, cloud, and operations design.
High-density AI data halls
Infrastructure environments shaped around GPU, networking, storage, and facility operations.
GPU rack infrastructure
Dense compute planning for model training, inference, and enterprise AI workloads.
Hybrid cloud operations
Control planes and operating models connected to secure enterprise data center environments.
Global reach,
local implementation.
Prognity supports infrastructure and AI platform delivery across India, the United States, Canada, and an expanding United Kingdom focus.
- Facility and cloud architecture
- GPU infrastructure planning
- Secure hybrid connectivity
- Operations and handover
Infrastructure specifications
The details that matter when data centers become the foundation for AI workloads.
GPU-Ready Design
Compute, networking, storage, power, and cooling decisions aligned to training and inference workload profiles.
High-Density Readiness
Facility and rack planning for dense AI infrastructure, including thermal strategy and operational maintainability.
Secure Operations
Network segmentation, access control, monitoring, and operational processes designed for enterprise environments.
Capacity Planning
Growth paths for clusters, storage, networking, and support operations without locking teams into brittle designs.
Regional delivery focus
Advanced capabilities
Dedicated Clusters
Isolated compute environments designed around workload, security, and operational boundaries.
Provisioning Workflow
Repeatable setup patterns for GPU nodes, storage, networking, observability, and access.
Operational Monitoring
Monitoring and alerting designed for facilities, infrastructure, and workload health.
Cost Governance
Capacity, utilization, and procurement planning that keeps infrastructure decisions visible.
Framework Support
Infrastructure patterns for PyTorch, TensorFlow, JAX, and custom AI application stacks.
Hybrid Connectivity
Network and cloud connectivity patterns for distributed enterprise operations.
Scale AI with enterprise infrastructure
Design the facility, IT, and cloud foundations before AI workloads become operationally critical.