Data center and AI infrastructure intelligence
The physical layer powering the AI era.
The explosion in artificial intelligence workloads has triggered the largest wave of data center construction in history. Hyperscale operators are building campuses measured in gigawatts. Cloud providers are competing for sites with available power and fiber connectivity. Sovereign AI initiatives are driving government-backed compute infrastructure across Europe, the Middle East, and Asia. Capital expenditure runs to hundreds of billions annually.
But building a data center has become dramatically harder. Power is the binding constraint. Grid connection timelines stretch to five or more years. Water availability for cooling is increasingly contested. Meanwhile, liquid cooling is becoming standard for AI workloads, on-site generation is being explored as a grid bypass strategy, and the boundary between data center and power plant is blurring.
Delphidata tracks data center and AI infrastructure from site identification through construction to operation. Our knowledge graph connects facilities to their power suppliers, cooling systems, fiber connectivity, construction contractors, and operators. The data model captures facility type, IT load capacity, power usage effectiveness, cooling technology, power sourcing strategy, and connectivity infrastructure.
What Delphidata tracks.
Structured data across the full value chain.
Data center projects
Hyperscale, colocation, wholesale, enterprise, edge, and sovereign AI categories. Mapped with IT capacity (MW), total power draw, site area, cooling technology, PUE target, and development timeline.
AI compute infrastructure
Purpose-built GPU/TPU clusters, AI training facilities, and inference deployment sites. Connected to chip architectures and cooling technologies they require.
Power and energy sourcing
Grid connection capacity and timeline, renewable energy PPAs, on-site generation (gas turbines, fuel cells, small nuclear), and battery storage.
Connectivity infrastructure
Submarine cable landing stations, terrestrial fiber routes, internet exchange points, and network fabric connecting campuses to cloud regions.
Supply chain
Server and GPU procurement, cooling system manufacturers, power distribution equipment, and construction/engineering firms specializing in mission-critical facilities.
Who uses this intelligence.
Data center operators and developers
Track competitor capacity additions, identify markets with available power and connectivity, and monitor permitting and grid connection timelines.
Power companies and utilities
Forecast load growth from data center demand, plan grid reinforcement, and identify behind-the-meter generation and storage opportunities.
Equipment and construction companies
Monitor the project pipeline to forecast demand for cooling systems, power distribution, rack infrastructure, and construction services.
Investors
Screen data center opportunities using structured data on power availability, grid connection status, pre-leasing commitments, and competitive supply.