AI

Predictive Monitoring & Anomaly Detection

We use machine learning models to analyze multi-modal sensor data—temperature, vibration, airflow, energy use—and detect patterns that signal early-stage failures. Our AI helps operators move from reactive firefighting to proactive issue prevention.

Workload-Aware Control Optimization

AI models dynamically optimize how workloads are scheduled based on real-time energy pricing, thermal capacity, and operational risk. This reduces both carbon emissions and operational costs while maintaining service-level performance.

Robotics Perception & Autonomy

Our robots rely on AI for computer vision, path planning, and decision-making. Whether inspecting server racks, identifying LED fault indicators, or swapping hardware, our AI ensures the robot sees, understands, and acts with precision.

Multi-Agent Orchestration

We use large language models (LLMs) and agent-based frameworks to create intelligent workflows across our system. Agents can coordinate data center responses, generate reports, and even control robotic actions based on structured logic and sensor feedback.

Digital Twin & Simulation

AI helps us build and maintain real-time digital twins of entire data center environments. We simulate power, thermal, and operational behavior to forecast outcomes and support better planning decisions.