From Reactive to Predictive: How AI Transforms Maintenance
Treon Flow - a simple, scalable and mobile-first way to keep assets running. Learn how AI alerts reveal issues instantly and guide technicians through fixes, helping your team move towards true uptime, and how Treon Make enables deeper diagnostics and advanced analytics when you want to progress to higher-level insight and optimization.
What you'll learn:
- Evaluate Treon solutions for predictive maintenance and find the right fit for your assets
- The most common barriers to enabling predictive maintenance
- The real business impact of predictive maintenance
- How AI predicts failures earlier to cut costs and downtime
- How companies use Treon Connect solutions to digitalize their maintenance operations
If you have used or are using Amazon Monitron, you’ll see how Treon Connect supports your long-term strategy, expanding coverage, building on your existing installations, and evolving towards a unified, scalable predictive maintenance architecture.
Speakers
Tom Nordman, SVP Sales at Treon plus a guest speaker to be announced.
5–6 pm (Central European Time)
11–12 am (Eastern Standard time)
11 am–12 pm US Eastern (EST)
8–9 am US Pacific (PST)
Frequently Asked Questions
Who is the webinar designed for?
The webinar will be most valuable to manufacturing and consumer goods companies that rely heavily on material handling equipment in their facilities.
Previous experience with AWS or Amazon Monitron technology is not necessary, but if you are familiar with them, you will feel right at home.
Is there going to be a recording available after the webinar?
Yes, we will provide a recording of the webinar as well as the slides to everyone who signed up for the webinar.
Can I send questions beforehand?
Yes, you can either ask questions during the webinar or send them beforehand to tom.nordman@treon.fi
Is this a sales call?
While we are discussing the topic of predictive maintenance of material handling equipment through our Treon Connect platform, we believe the webinar will be valuable even if you have no intention or need to invest in predictive maintenance any time soon.