ommercial Equipment Manufacturers:
Create New Revenue Streams with Edge ML Anomaly Detection
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Should you run AI in the cloud or at the edge?
Most industrial equipment manufacturers are asking this question as they explore how anomaly detection can transform their operations and create new revenue opportunities.
The answer isn't either/or - it's both. The most successful deployments use edge processing for real-time decisions close to your equipment, while leveraging cloud capabilities for model training, updates, and monitoring.
Watch this fireside chat featuring experts from Blues and Edge Impulse as they share real customer stories and practical insights on deploying AI-powered anomaly detection that delivers measurable business value.
In this on-demand webinar you'll learn:
- Edge vs. Cloud Decision Framework - When to process data locally versus in the cloud, and why hybrid approaches often win
- Model Monitoring & Evolution - Why deployed models need ongoing updates and how to architect for changing production environments
- Connectivity Strategy - Minimizing data transport costs while maintaining the connectivity needed for model updates and monitoring
Watch now to discover how leading manufacturers are using edge ML anomaly detection to reduce costs, improve uptime, and create new service offerings.
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Our Speakers
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Jim Hassman
President and CRO at Blues
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Alessandro Grande
Director of Edge AI Developer Growth at Edge Impulse (A Qualcomm Company)
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Alexis Susset
Director of Product Management at Edge Impulse (A Qualcomm Company)
The opinions expressed in this presentation, in the included slides, and in transcripts are solely those of the presenters and not necessarily those of Blues.
Blues does not guarantee the accuracy or reliability of the information provided herein.