Kando and Paperspace Partner to Bring Advanced Machine Learning to Municipal Systems Monitoring

This article was originally published on the Paperspace Blog. To see the original article, click here

Kando, a technology company providing smart wastewater management solutions to municipal utilities, has integrated Paperspace’s Gradient machine learning platform to bolster its leading Clear Upstream wastewater event monitoring system.

With the partnership, Kando brings a state-of-the-art machine learning toolset and MLOps platform to its technology stack.

Machine learning is helping IoT companies leverage automation and analysis for big data solutions. Kando is taking advantage of this trend by deploying ML solutions to identify pollution risks, pinpoint sources of pollution, and evaluate impacts that require a swift emergency response to keep cities and residents safe.

As a result, clients such as El Paso Water and Clean Water Services of Portland are able to gain real-time, continuous monitoring.

Todd Feinroth, VP of Sales for Paperspace, said: “We’re pleased to partner with Kando to bring best-in-class machine learning tools to critical municipal infrastructure monitoring. We look forward to helping Kando build its machine learning capability and deliver leading solutions to wastewater utilities around the world.”

“Our partnership with Paperspace will boost our system’s advanced analytics so that we can better enable cities to remotely and continuously control their wastewater quality. Accordingly, we will begin to see greater wastewater reuse, cleaner environments, and healthier communities.” – Ari Goldfarb, Kando CEO

Working together, Kando and Paperspace will bring advanced machine learning capabilities to the management of environmental risks and public health.