Industrial manufacturers face, on average, about 800 hours of unplanned downtime every year, or more than 15 hours per week, according to a recent report. The cost of unexpected troubleshooting, estimated at $50 billion yearly, results in lower productivity and lost revenue. Most companies are still manually troubleshooting, but ControlRooms.ai, an Austin, Texas-based startup, wants to change that.
The company has developed an AI-powered analytics application to automate the industrial 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 same process today as it was in 1980,” Omar A. Talib, co-founder and president of ControlRooms.ai, told TechCrunch. “The traditional alarm does not provide specific insight into what may be causing problems, so it can often result in long and inefficient searches for potential errant ‘trends.’ These traditional exercises — conducted in the spirit of troubleshooting — are exhausting and inefficient.”
The startup claims its turnkey troubleshooting platform enables users to get up and running “within a week without changes to their current systems” to minimize downtime, according to the company. 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 a company that delivers AI solutions to energy producers. ControlRoom.ai launched its first product last year and has five customers using it.
“A chemical customer uses ControlRooms to track over 10,000 asset parameters in real time, such as pressures, volumes and temperatures, to decrease reliability violations that degrade asset health,” Talib said.
He believes ControlRooms sets itself apart from competitors because its application isn’t just AI-powered. It’s “purpose-built for the process engineers, operations engineers, and operations supervisors who work in these heavy industry facilities,” unlike general-purpose AI platforms, according to Talib.
It plans to use the new capital to accelerate its product development and go-to-market in heavy industries, including chemical, petrochemical, energy and materials facilities in 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 how to incorporate generative AI capabilities into its platform in the near future. “Imagine if the techniques that enabled the conversational intelligence of ChatGPT-4 and its competitors could be applied to industrial time-series data,” the CEO said, adding that it would allow unprecedented predictive applications like letting operations personnel see around corners and avoid surprises.