Veracio, a bigger vision for smarter data at a smaller footprint by Boart Longyear

February, 2023

Boart Longyear announced the launch of Veracio, a brand-new separate entity for the company Geological Data Services.

Veracio’s technologies and platform are set to transform the mineral exploration process by empowering miners to dig deeper into data, accelerating exploration, and making better, faster decisions that result in economically efficient operations and reduced waste. ‘Boart Longyear’s new entity is well-grounded on a decade of testing and development in sensing, automation, and artificial intelligence (AI) technologies’, the company’s representative said.

As the demand for critical metals continues to rise, the need for efficient and accurate mineral exploration has never been greater. The mining industry is facing the pressure of reducing the time from discovery to mineral extraction. Powered by Boart Longyear’s award-winning Geological Data Services integrated technology platform, Veracio is well-positioned to support the growing global need for critical minerals by championing an approach to orebody science based on speed and sustainability. Veracio will support the exploration teams to discover new mineral deposits, increase their success rates, and reduce costs.

Veracio leverages key digital sensing platforms and AI that helps miners move beyond the borehole and see the entire orebody in fine detail. ‘AI solutions that improve and automate improved understanding of the earth and orebodies and deliver improved solutions for mining activities across the value chain are one critical component’, reads the company’s official press release.

Other key factors are data capture and intelligence platforms including TruScan™, an in-field sample sensing platform; TruSub™, a rod string system; and TruProbe™, which allows for driller deployable downhole sensing without a logging truck.

 

There is also a foundational, integrated cloud platform that gives teams anywhere in the world access to these technologies, enabling them to access orebody data in near-real time, at a higher definition, and with lower sampling error.