Tractian gets $45M to expand AI monitoring of industrial machinery

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Tractian gets $45M to expand AI monitoring of industrial machinery

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Tractian, an industrial asset monitoring company that uses AI to predict mechanical failures, has announced a $45 million series B funding round led by Boston-based venture capital firm General Catalyst and Next47.

The funding will enable Tractian to expand its AI capabilities, grow its research and development (R&D) team and enter new industrial verticals. The round follows a $15 million series A round in 2022 and positions Tractian for further growth.

Founded in 2019 by Igor Marinelli, Tractian uses sensors, edge computing hardware, and AI models to monitor industrial machines and identify potential failures based on vibrations and frequency patterns. The company’s AI analyzes machines’ “fingerprints” to detect specific mechanical issues like wear, imbalance and misalignment. 

Tuning in to the right frequency

“They all have very specific waves and frequencies that we can identify, no matter if this motor is inside a pulp and paper plant, no matter if it’s an automotive plant. If there’s a motor of that manufacturer, of that OEM, it’s going to have that specific frequency,” said Marinelli in a phone call with VentureBeat. Marinelli, whose background is in industrial maintenance, says he founded Tractian to help companies eliminate downtime, anticipate failures and extend the lifetime of their assets. 


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Tractian manufactures its own sensors and hardware to ensure high uptime and reliability in harsh industrial environments. The company currently has over 500 customers, representing roughly 1,000 manufacturing plants across industries like food and beverage, automotive, oil and gas, and facilities management.

“We have our own factory, we manufacture our own hardware, we’re 100% verticalized. We have the patents on the hardware, the patents in the models,” said Marinelli. The company estimates its technology currently impacts around 5% of global industrial GDP, based on its customer base.

Marinelli says that it’s relatively straightforward to evaluate a prospective maintenance solution, “whether this is going to add top-line revenue or reduce some of the costs.”

“Our average savings … per machine is $6,000 a year,” he told VentureBeat.

R&D, expansion and AI training will benefit from new funding 

With the new funding, Tractian plans to expand into different verticals and continue refining its AI models as well as continue its strong focus on R&D. The company currently has nearly 200 R&D engineers focused on data science, data engineering, hardware engineering and firmware development.

Tractian’s AI models are tailored specifically to different machine types and industrial verticals. The company says industry-specific AI is key to achieving high accuracy in failure prediction. With 3,000 models already deployed and able to detect different types of failures, the Tractian platform will continue to adapt to new systems using feedback from its users.

“The more that you add data, the human feedback loops happen” and the better your system gets over time, said Marinelli. “And the more competitive advantage you have,” he added, “because you have a massive database of failure that’s been cataloged and labeled by the user.”

While Tractian leverages mobile networks for connectivity, the company does not rely on WiFi to ensure uptime. Tractian embeds its own connectivity in sensors that automatically select the best available carrier. Tractian says one of the main challenges with its AI is getting accurate feedback from customers to improve models. Sometimes customers ignore failures flagged by the AI when the failure can be worked around.

“We want to be world-class at manufacturing and we can’t do so without a predictive maintenance solution. We tried to build this internally but were left with a mess of data and no easy way to take actions on it,” said Luis Moncada, the Maintenance Manager at Johnson Controls in a release on Monday. “I believe the future is highly personalized with AI at the center — I want my alerts to be based on my utilization, my equipment and my way of stressing my machine. Tractian is simply more agile at applying new technologies and they are far more collaborative in coming up with new ideas and implementing them.”

The series B funding marks an important step in Tractian’s mission to optimize asset uptime for industrial companies around the world. The new capital will enable Tractian to significantly expand its AI-based asset monitoring solutions and help more organizations reduce downtime and maintenance costs.

Marinelli said he draws on his own experience of his father working in the maintenance business. “He started his career as a maintenance technician, and then maintenance supervisor, then maintenance coordinator,” said Marinelli. “I lived this from my childhood. And when I went to work in industry to see it myself, I got passionate about this challenge.”

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