Optimizing HVAC Model Management with Azure ML Deployment
Client: Large HVAC and facility management company | Solution: Azure ML pipeline for MLOps and telemetry integration
Sales Needed Predictable, Efficient Model Lifecycles
The client, a large HVAC and facility management company, struggled with manual model deployment and inconsistent telemetry handling across its distributed assets. With no centralized process in place, engineers faced delays and inefficiencies, impacting the accuracy of HVAC system predictions and the overall operational workflow.
Solution
Calsoft implemented an Azure-based MLOps architecture, integrating telemetry data, model pipelines, and digital twin workflows into a governed lifecycle. The deployment standardized processes, improved model training cycles, and created more reliable, predictable system performance across multiple sites.
- Structured sensor data ingestion for consistent model input
- Streamlined model training and evaluation with Azure ML
- Automated deployment via Azure DevOps CI/CD pipelines
- Integrated digital twin models for real-time asset monitoring
Business Value
To Know More
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