Agentic AI Data Center Power & Cooling Planner

Infrastructure Controls Direct Manipulation

Deployment Architecture Presets

Active Agents 150,000

Autonomous reasoning workers running concurrently

Steps per Task (Reasoning Loop) 12

Tool executions, context rollouts, and self-checks

PUE Efficiency Factor 1.15

Total Facility Power / IT Equipment Power

Cooling Mode

Determines water evaporation rate per megawatt-hour

Substation Capacity 96.5 MW

Dedicated regional utility feed allocation

Facility Impact & Grid Telemetry Status: Live Engine

Total Power Demand

84.5

Megawatts (MW)

Daily Water Consumption

1,420,000

Gallons / 24 Hours

Substation Headroom

12.4%

Reserve before cutoff

Grid Stress Index

High

Local utility reliability tier

Operating State: Regional Multi-Agent Hub running 150,000 agents with 12 iterative reasoning steps. Liquid hybrid cooling maintains thermal equilibrium at 1.15 PUE. At 84.5 MW power draw, the substation headroom is compressed to 12.4%, leaving minimal buffer for heatwaves or auxiliary loads.

Export includes 24h hourly projections

Research Grounding & Infrastructure Context

WIRED's investigation highlights how autonomous AI agents deviate from standard search and single-turn queries: rather than a one-shot 0.3 Wh response, agentic workflows execute multi-step planning loops, continuous context maintenance, and tool integrations that multiply compute demand by 10× to 40×. This surge is driving the rapid buildout of 100MW+ clusters, direct-to-chip liquid cooling systems, and intensive water evaporation requirements.