Trane Technologies AI Lab

Development of technology using real-time data and advanced AI algorithms to enable the automated optimization of building assets using live equipment commands and control strategy assessments.

Development of virtual agents designed to process and contextualize large volumes of internal and external data to deliver data visualization, reasoning, and informed human-in-the-loop automated actions using advanced LLM technology, with responsible AI guardrails and mechanisms to limit hallucination.

Advancement of deep learning models that can anticipate building needs with strong predictive performance, supporting improved real-time control strategies.

Ongoing optimization of high-performance tech stack with real-time data processing, continuous system checks, automatic model retraining, and robust multi-layered protocols.

Combining traditional neural networks with fundamental physics principles to enhance physical interpretability and support improvements in prediction accuracy and training data needs.

Development of algorithms designed to support emissions reduction efforts, integrating real-time and forecasted emissions signals to derive consumption patterns and help prioritize cleaner energy sources.