In this episode, Eigen Innovations Co-Founder and CEO Scott Everett joins us to discuss the role IoT plays in driving decision-making based on insights, rather than data. Scott speaks to the raw data produced by machine learning and AI technologies and what needs to be done to convert that data into actionable insights truly capable of changing daily workflow. Scott shares the challenges he’s seen working to educate customers on how IoT solutions and AI works and what advice he has for companies who have been struggling with those same challenges.

Scott also shares his experience developing the Eigen Innovations platform and what he’s learned introducing it to customers, as well as the approach he takes in generating meaningful data for customers.

Scott has dedicated his entire career to consulting in engineering and quality control applications. He co-founded Eigen Innovations in 2012 and has been working since that time to bring state-of-the-art technology to the factory floor, specializing in advanced industrial vision and machine learning. Scott is based in Fredericton, New Brunswick, Canada, and spends the majority of his time working with the product development team to evolve Eigen’s AI-enabled solutions as well as pitching the solution to Tier 1 manufacturers around the globe. He’s also in the process of completing his PhD studies in Mechanical Engineering.

Interested in connecting with Scott? Reach out to him on Linkedin!

About Eigen Innovations: Eigen Innovations supports and enhances quality assurance in industrial manufacturing with its unique AI-enabled industrial vision platform. Currently honing in on the automotive sector, Eigen tech has been deployed in several Tier 1 automotive supplier plants across multiple applications (plastic welding, glass soldering, windshield adhesive, etc.).

Key Questions and Topics from this Episode:(01:02) Intro to Scott

(03:56) What is vision data?

(05:20) Introduction to Eigen Innovations

(07:25) How do you approach conversations about transforming companies from being data-driven to analysis or insight-driven? Do you ever experience pushback against those ideas and how do you handle that?

(11:41) How do you educate companies on IoT and what it can do for them? Do you have advice for other companies that are struggling with that?

(14:16) What were the biggest challenges over the course of developing the platform and introducing it to customers?

(20:28) What’s your approach to generating data that actually changes a customer’s workflow?