CrossnoKaye has developed the ATLAS platform, an industrial operating system that utilizes physics-based machine learning to optimize energy consumption and operational efficiency in heavy industrial refrigeration systems. By transforming traditional facilities into smart, responsive assets, ATLAS enables up to 48% energy savings while reducing carbon emissions in the food and beverage sector.
Funding
Funding not disclosed
COFounders
Product
Problem
Heavy industrial refrigeration systems in the food and beverage sector often suffer from inefficient energy consumption due to outdated control systems and a lack of real-time optimization. Traditional facilities struggle to adapt to changing conditions, leading to increased energy costs and higher carbon emissions. Furthermore, reliance on manual adjustments and a shrinking talent pool exacerbates these inefficiencies.
Solution
CrossnoKaye's ATLAS platform is an industrial operating system that leverages physics-based machine learning to optimize energy consumption and operational efficiency in heavy industrial refrigeration systems. ATLAS transforms traditional facilities into smart, responsive assets by connecting them to an integrated suite of cloud applications. The platform uses real-time data and external factors like weather forecasts and utility rates to model power consumption and automatically implement ideal energy strategies. This approach enables facilities to reduce energy consumption by up to 48% while also tracking and reducing Scope 2 and Scope 3 carbon emissions.
Target Audience
The primary target audience includes companies in the food and beverage industry with heavy industrial refrigeration systems, particularly cold storage and food processing facilities, seeking to reduce energy consumption, lower carbon emissions, and improve operational efficiency.
Features
- Enterprise cloud platform with integrated suite of cloud applications
- Physics-based machine learning for real-time optimization of refrigeration systems
- Integration with external data sources (weather, utility rates, etc.) for predictive control
- Automated energy strategy implementation based on facility conditions
- Centralized industrial operating system extendable across entire organization
- Unified control narratives, process alarms, and ammonia response logic
- Standardized safety and compliance protocols for every site
- Real-time responses to physical onsite and external conditions
- Cloud-based infrastructure for enterprise governance and data visibility
- Continuous updates and improvements deployed across all sites
- SOC2-compliant control system with SSO, 2-Factor Authentication, live security patches, granular access controls, and data encryption