AI-powered PUE and cooling efficiency for GCC data centers. From real-time setpoint recommendations to long-term capacity planning, every decision is grounded in data.
Measured outcomes from production deployments across GCC facilities.
Average Power Usage Effectiveness improvement achieved within 90 days of full platform deployment. Measured against a certified pre-deployment baseline.
Reduction in total cooling energy consumption across production deployments. AI setpoint optimization delivers compounding savings over time.
Most Tabrid.ai energy optimization deployments reach breakeven within six months, driven by electricity cost savings in GCC markets.
Every capability is engineered for the operational realities of GCC data centres and logistics networks.
Real-time Power Usage Effectiveness and Coefficient of Performance dashboards give your operations team a live readout of energy efficiency — not a monthly report. Sub-second telemetry from PDUs, UPS units, and cooling infrastructure is aggregated into actionable PUE/COP metrics, with drill-down into the specific systems contributing to inefficiency at any moment.
Weather-adjusted cooling load forecasts account for GCC ambient extremes — summer temperatures above 45°C in Riyadh and Dubai add significant unpredictable load to cooling systems. The platform integrates local meteorological feeds with historical workload patterns to produce 24- and 72-hour cooling demand forecasts, enabling demand-response participation and proactive setpoint adjustment.
AI-driven chiller and CRAH setpoint recommendations reduce energy consumption while maintaining the thermal envelope required for SLA compliance. The optimization engine models the relationship between supply air temperature, IT inlet temperature, and workload distribution to find the lowest-energy operating point that keeps every rack within its thermal budget.
Automated energy consumption reports cover total facility usage, cooling subsystem breakdowns, and carbon footprint estimates aligned with GHG Protocol Scope 2 methodology. Scheduled reports are delivered to operations, finance, and sustainability stakeholders — ready for Saudi Vision 2030 disclosures, investor ESG requests, and tenant billing.
A structured, low-disruption deployment process designed to integrate with your existing infrastructure.
A certified Tabrid.ai engineer audits your facility's current energy profile, establishing a verified PUE/COP baseline that will be used to measure all future improvements.
Energy meters, temperature sensors, and flow sensors are installed across cooling infrastructure and IT load paths. Data streams are validated against utility billing to ensure accuracy.
The optimization engine begins issuing setpoint recommendations within the first week. Facility operators review and approve changes; the system learns from each accepted or overridden recommendation.
As the AI accumulates operational history, optimization recommendations become more precise. Quarterly business reviews compare achieved savings against the certified baseline.
Schedule a personalised demo and discover how this module integrates with your existing infrastructure to deliver measurable results.
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