Lean TECHniques Invests In Unsupervised Machine Learning Company
December 19, 2020
3 minute read
Urbandale, Iowa: January 19, 2021 – Lean TECHniques, a software consultancy, has announced a strategic investment in Boon Logic, an unsupervised machine learning company. The strategic investment allows Lean TECHniques to advance its expertise in digital transformation with Boon Logic’s autonomous learning products.
“Machine learning and artificial intelligence is the next tech wave, and we want to be there,” explained Brandon Carlson, founder of Lean TECHniques. “We were intrigued by Boon Logic because they are one of the few companies with scalable off-the-shelf machine learning products that offer a variety of deployment architectures, giving them an advantage when it comes to monitoring deployed assets wherever they may physically sit. Everyone else is doing custom solutions that are ridiculously expensive and time-consuming to build, which is unrealistic for most companies. Boon Logic’s products are quick to deploy and start learning within minutes.”
“This is a true strategic partnership,” added Grant Goris, CEO of Boon Logic. “We are gaining the support capabilities of Lean TECHniques, and they now have access to machine learning experts and cutting-edge technology. Together, our two companies can build a portfolio of rinse-and-repeat products across our customer bases.”
Boon Logic offers two autonomous learning solutions. Amber is a type of predictive maintenance monitoring that detects performance anomalies in equipment, and Avis is a form of visual inspection and quality assurance for manufacturing. Both are enabled by Boon Logic’s unsupervised machine learning technology, the Boon Nano, which performs millions of inferences in seconds.
“Machine learning can be hard for an organization to grasp and apply to a real use case, but Boon Logic’s unsupervised products have tangible outcomes that appeal to customers. With our background in deploying and supporting platforms, we can now offer customers a complete product and service integration package,” explained Danielle Brommer, chief growth officer for Lean TECHniques.
Boon Nano, which performs 1,000 times faster than competitive approaches in the unsupervised machine learning space, enables both training and inference at the edge – something that algorithms such as K-means cannot support in production environments.
In addition, this speed generates real-time alerts whenever a variance is detected and notifies the user which features contributed to the deviation from “normal operation,” even amongst hundreds or thousands of variables.
“We want our engineers to keep growing, and machine learning is a new frontier for them. This investment allows our team members to work on Boon Logic’s proprietary solutions as well as help our customers uncover new applications for this technology,” said Tim Gifford, chief innovation officer for Lean TECHniques.
Beyond Boon Logic’s current manufacturing focus, the two companies are exploring opportunities to offer predictive analytics to other sectors. Potential markets include agricultural equipment, wearables, automotive engines and other industrial equipment monitoring applications.