Industrial manufacturers face, on average, about 800 hours of unplanned downtime every 12 months, or greater than 15 hours per week, based on a recent report. The fee of unexpected troubleshooting, estimated at $50 billion yearly, ends in lower productivity and lost revenue. Most corporations are still manually troubleshooting, but ControlRooms.ai, an Austin, Texas-based startup, wants to alter that.

The corporate has developed an AI-powered analytics application to automate the commercial troubleshooting process. Today, the startup announced that it has raised an oversubscribed $10 million Series A round, led by Origin Ventures with participation from Amity Ventures, Tokio Marine Future Fund, S3 Ventures, GTM Fund, Alpha Square Group and FJ Labs. It has now raised $13.75 million.

Troubleshooting for heavy industries like chemical and energy plants is “virtually the identical process today because it was in 1980,” Omar A. Talib, co-founder and president of ControlRooms.ai, told TechCrunch. “The normal alarm doesn’t provide specific insight into what could also be causing problems, so it might often end in long and inefficient searches for potential errant ‘trends.’ These traditional exercises — conducted within the spirit of troubleshooting — are exhausting and inefficient.” 

The startup claims its turnkey troubleshooting platform enables users to rise up and running “inside per week without changes to their current systems” to attenuate downtime, based on the corporate. Its AI predicts manufacturing plant behavior and detects potential problems before engineers or control room operators notice them. 

ControlRooms.ai was co-founded in 2021 by CEO Monte Zweben, an AI expert and serial entrepreneur, and Talib, who previously worked for an organization that delivers AI solutions to energy producers. ControlRoom.ai launched its first product last 12 months and has five customers using it. 

“A chemical customer uses ControlRooms to trace over 10,000 asset parameters in real time, reminiscent of pressures, volumes and temperatures, to diminish reliability violations that degrade asset health,” Talib said. 

He believes ControlRooms sets itself other than competitors because its application isn’t just AI-powered. It’s “purpose-built for the method engineers, operations engineers, and operations supervisors who work in these heavy industry facilities,” unlike general-purpose AI platforms, based on Talib. 

It plans to make use of the brand new capital to speed up its product development and go-to-market in heavy industries, including chemical, petrochemical, energy and materials facilities within the U.S., Asia (China, Japan and South Korea), Germany and the Middle East. 

The startup, which has 15 full-time employees on its team, is currently conducting extensive R&D on incorporate generative AI capabilities into its platform within the near future. “Imagine if the techniques that enabled the conversational intelligence of ChatGPT-4 and its competitors may very well be applied to industrial time-series data,” the CEO said, adding that it will allow unprecedented predictive applications like letting operations personnel see around corners and avoid surprises.