Industry 4.0 and the push towards manufacturing automation hinges on optimization. As manufacturing plants become more digital, these facilities need a way to better access, optimize and act on disparate data.
From its home base in Raleigh, ndustrial.io just raised a $6 million Series A round to do just that.
Through both its software (called contxt) and a team of field engineers, ndustrial works to aggregate and optimize data across a facility to improve energy efficiency. Coincidence Peak, one of the startup’s applications, helps manufacturing facilities forecast when electric grid prices are at their highest so these facilities can reduce power consumption.
This is particularly important in large factories, where upwards of 99% of data can be discarded before any useful information is gleaned and new processes can be implemented.
For Vincent Pichon, ENGIE New Ventures’ Investment Director, ndustrial’s energy efficiency platform is helping create more sustainable manufacturing practices. “Clean energy isn’t just about producing clean electricity; it’s also about reducing the amount of electricity used per unit of production,” he added.
“Their tangible application of machine learning for energy efficiency and process improvement stands apart,” said Clean Energy Ventures’ co-founder Daniel Goldman. “We believe their technology has the potential to materially impact carbon emissions in older industrial facilities across a wide range of sectors, and we’re looking forward to helping them scale their innovative technology.”
Sheeraz Haji, Senior Advisor, ENGIE New Ventures added, “Industrial facilities are incredibly complex behind the utility meter. Each site has a unique combination of systems and software, often built up over many years. That reality makes aggregating data and modeling across multi-site businesses hugely challenging, but also extremely important in order to reduce energy.”
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