Mining AI firm raises $1.2m to speed product roll-out

Funding to advance trials in Canada and Zambia.

Canadian mining AI firm Rithmik Solutions says US$1.2 million in new funding from Chrysalix Venture Capital and Ecofuel Fund will help speed commercialisation of its flagship asset health tracking product, said to be undergoing “real-time field trials” in Canada and Zambia.

The four-year-old British Columbia-based Rithmik said its Rithmik Asset Health Analyzer (AHA), in development for three years, spearheaded its “mission is to create the world’s most advanced and reliable analytical tools for mobile mining equipment”.

Rithmik co-founder and CEO Amanda Truscott said AHA application results included detection of faults “hours to months in advance of major failures in multiple types and brands of mobile mining equipment across vastly different geographies”.

“Our system has also proven able to uncover chronic inefficiencies along with gaps and inconsistencies in the data itself,” she said.

Rithmik is among more than a dozen portfolio investments for the US$120m Chrysalix RoboValley Fund, created by Chrysalix and the Netherlands-based Delft University of Technology’s RoboValley centre for robotics commercialisation. The fund was set up to “identify, invest in and commercialise breakthrough robotics technologies” and also invest in Industry 4.0 technologies that improve industrial processes and resource use, according to the partners.

Fund backers have included Teck Resources, South32, Mistletoe Venture Partners International, PETRONAS, Severstal, Delft University, Mitsubishi Corporation, Caterpillar, J-Power and Hyundai Motor Company.

“We were impressed by the Rithmik team’s deep technical experience in the space of mobile mining equipment data, across equipment types and OEM brands, and that experience has strongly resonated with their early customers,” said Alicia Lenis, Chrysalix Venture Capital vice president.

“And when we looked at their approach, which is a scalable AI-first solution that accounts for the extreme variability in mines, we see significant potential that they can crack this tough problem for mining companies.”


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