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Earth AI Secures $20M in Oversubscribed Series B Round for AI-Driven Mineral Exploration

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Highlights

  • Earth AI raises $20 million to expand AI-powered mineral exploration with a remarkable 75% discovery success rate.
  • The startup leverages AI and proprietary drilling technology to identify greenfield mineral deposits in untapped areas.
  • The company aims to disrupt the $10 trillion critical mineral market by reducing exploration costs and timelines.

Earth AI, a startup revolutionizing mineral exploration with artificial intelligence, has raised $20 million in an oversubscribed Series B funding round led by Tamarack Global and Cantos Ventures, alongside notable investors like Y Combinator and Scrum Ventures. The funding will bolster Earth AI’s capacity to explore over 50 new sites and achieve drilling rates of 100,000 meters annually at an industry-leading cost of approximately $100 per meter. Founded in 2017, the company leverages its AI-powered Mineral Targeting Platform (MTP) and proprietary mobile low-disturbance drilling technology to achieve a remarkable 75% discovery success rate—vastly outperforming the industry average of 0.5%.

The company made the announcement via press release (opens in a new tab).

Earth AI’s business model focuses on identifying greenfield mineral deposits, validating them through efficient drilling, and selling multi-billion-dollar mining rights to major players in the mining sector. The company stands out by using AI trained on massive continental-scale datasets to locate resources in untapped areas, a critical advantage as global demand for minerals like palladium and gold surges due to the energy transition. Recent discoveries include a significant palladium system in Australia and a gold system in New South Wales.

Opportunities and Challenges

Earth AI’s approach addresses inefficiencies in a fragmented exploration industry, reducing costs and timelines while meeting the mining sector’s growing need for critical minerals. Its potential to disrupt the $10 trillion critical mineral market is substantial. However, challenges lie in scaling its operations, maintaining its AI’s accuracy as projects grow, and navigating regulatory and environmental hurdles in an industry often scrutinized for its ecological impact.

Furthermore, the reliance on selling mining rights to large companies introduces dependency risks.

With its innovative model and proven success rate, Earth AI is well-positioned to redefine mineral exploration, but it will need to navigate execution challenges carefully to maintain its competitive edge in a rapidly evolving market.

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