Glacian provides a Physical AI platform that uses modular digital twins and multi‑objective optimization to continuously model and adjust data‑center cooling systems. By operating vendor‑agnostically and without major construction, it reduces cooling‑related power consumption, enabling higher compute density while cutting energy costs and supporting sustainability goals.
Funding
Funding not disclosed
Founders
Product
Problem
Data centers consume a large portion of their total electricity on cooling systems, limiting available compute capacity and increasing operational costs and carbon emissions. Traditional cooling controls are often siloed, vendor‑specific, and lack the ability to balance performance, energy use, reliability, and compliance simultaneously.
Solution
Glacian offers a Physical AI platform that applies modular digital twins and multi‑objective optimization to data‑center cooling infrastructure. The engine continuously models and evaluates trade‑offs across cooling performance, power draw, energy efficiency, reliability, regulatory compliance, and carbon impact, delivering balanced adjustments in real time. By operating independently of any specific DCIM or hardware vendor, the solution can be overlaid onto existing monitoring and control systems without major construction or utility permits. The platform enables data‑center operators to increase AI compute density while reducing cooling‑related power consumption, delivering measurable energy savings and supporting sustainability goals.
Target Audience
Primary customers are hyperscale cloud providers, enterprise data‑center operators, and colocation facilities seeking to expand compute capacity while lowering cooling energy costs and meeting sustainability targets.
Features
- Modular digital twin models that replicate the thermodynamic behavior of cooling equipment and airflow pathways
- Multi‑objective optimization engine that simultaneously targets power, energy, reliability, compliance, and carbon metrics
- Real‑time control intelligence that adjusts cooling setpoints and fan speeds based on live sensor data
- Vendor‑agnostic integration layer compatible with any DCIM, monitoring platform, or cooling hardware
- Continuous performance monitoring and reporting dashboard for operational visibility and compliance tracking
- Scalable architecture that supports incremental deployment across single racks to whole‑facility implementations