From Monitoring to Autonomic Operations
Data center efficiency is influenced by the maturity of digital and AI management systems.
Kriterion supports a path from reactive monitoring toward predictive, integrated and self-optimising operations.
Data Centers
AI-enabled operations for critical infrastructure.
Kriterion helps data center teams improve operational efficiency, reduce risk and manage complex infrastructure through AI-enabled asset intelligence.
19%
generator fuel and carbon reduction
17.44%
HVAC maintenance saving
18.12%
battery maintenance saving
Deep Digital Twins for Complex Sites
Deep Digital Twins can model heterogeneous asset fleets across generating capacity, cooling infrastructure, energy storage and power distribution.
AI models help teams predict risk, improve maintenance scheduling and optimise parameters while staying within safe operating conditions.
Data Center Use Cases
These use cases sit at the centre of the offering, turning operational data into maintenance, fuel, energy and network actions.
Power and Backup Systems
Deep Digital Twins support transformers, generators, UPS, DC plant, PDUs and storage systems with predictive asset health and performance insights.
Energy Efficiency
AI-optimised parameters can minimise energy consumption while adhering to safe operating conditions and supporting lower operational expenditure.
HVAC and Thermal Risk
Predictive scheduling and temperature control intelligence help reduce reactive repairs, improve response times and lower thermal risk.
Network and ASN Monitoring
External IP prefix and ASN monitoring provides reachability checks, BGP-aware insight, site-level health and SLA-grade reporting.
Operational Capabilities
Integrated DCIM Intelligence
AI can be applied to DCIM-style data lakes to support prediction, service management and near-real-time optimisation.
Scalable Site Adoption
The same heterogeneous asset fleet approach can support regional, access and edge infrastructure.
High-Frequency Operational Data
Minute-by-minute raw data and store-and-forward resilience help AI deliver real-time predictive insight.
Case Studies
Generator Efficiency
An anonymised infrastructure deployment showed a 19% reduction in fuel expenditure and carbon emissions by improving generator efficiency.
View case study results
HVAC Maintenance
Predictive HVAC scheduling reduced maintenance spend by 17.44% by decreasing corrective repairs and improving technician response.
View case study results
Battery Risk Reduction
Battery maintenance spend reduced by 18.12%, while AI-enabled temperature control improved setpoint adherence by 4.7%.
View case study results