Webinars

Machine Learning & Automation for Grain Operations 

July 22, 2026 
3:00 p.m. CDT

Machine learning and automation are becoming increasingly common topics in grain operations, but what do they actually mean in practice? This webinar provides a practical introduction to machine learning and automation through the lens of grain handling operations. Attendees will gain a better understanding of how these technologies work, where they are being applied today, and the potential impacts on safety, workforce utilization, and operational efficiency. 

Key Takeaways:

• Machine Learning Fundamentals 
  Understanding what machine learning is, how it differs from traditional automation, and why it is becoming an important topic in grain handling. 
• Vision Systems, Sensors, and Safety 
  Exploring how machine learning, cameras, and sensors work together to support operational awareness, consistency, and safety. 
• Automation’s Role in Grain Operations 
  Examining current examples of automation in grain handling and bulk loading applications and where the technology is being utilized today. 
• Workforce Impacts and Labor Considerations 
  Discussing how facilities are using automation to address labor challenges, reduce exposure to hazardous tasks, and support workforce effectiveness. 
• Implementation Considerations and Operational Realities
  Evaluating common challenges, limitations, and factors that influence whether automation is a practical fit for a facility’s goals and operations.  

About the Speakers

Tom Boehm
President/CEO
RAYHAWK Technologies

Tom Boehm leads RAYHAWK’s strategic direction and innovation in autonomous railcar loading systems that enhance safety and operational efficiency in heavy industrial applications. He also serves as the President & CEO of Team Power Solutions, where he oversees business growth and delivery of electrical, automation, and technical solutions for commercial and industrial clients.

John Thuringer
Machine Learning Specialist
RAYHAWK Technologies

John Thuringer is responsible for the computer vision pipeline at RAYHAWK. His work involves ongoing analysis of deep learning architectures and model performance in dynamic outdoor environments where accuracy, precision, and speed are critical. He also developed a camera system capable of detecting bidirectional motion at speeds approaching zero.