Terra AI has raised $20 million in Series A funding to expand its artificial intelligence platform for mineral and reservoir exploration, a move that positions the Palo Alto company at the center of growing demand for faster resource development. The round was led by Khosla Ventures and included strategic backing from BHP Ventures, the venture capital arm of global resources group BHP. The financing comes as mining, energy, geothermal, and carbon storage developers face mounting pressure to locate and evaluate subsurface assets with greater speed, accuracy, and capital discipline.
Funding and Strategic Backing
The company said the new capital will support wider deployment of its generative geological modeling technology across mining, enhanced geothermal, and carbon storage applications. Terra AI’s platform is designed to reduce uncertainty in subsurface decision-making by integrating exploration, geophysical, geochemical, drilling, and reservoir data into probabilistic models. In practical terms, the company aims to help operators decide where to drill, which assets to prioritize, and how to assess project economics earlier in the development cycle.
The financing also signals continued investor interest in technologies that could modernize one of the slowest and most expensive stages of the natural resources value chain. Axios reported that BHP Ventures contributed $4 million to the round after BHP tested Terra AI’s technology on a mining project last year. Terra AI’s previous backers include Rio Tinto, Storyhouse Ventures, Plug and Play, the TomKat Center for Sustainability, and Climate Capital, according to the company’s announcement and related coverage.
Technology and Market Need
Terra AI’s core proposition is that conventional exploration remains too fragmented, too slow, and too dependent on incomplete interpretations of underground conditions. Its patented technology generates large numbers of geologically realistic 3D models, allowing project teams to compare possible subsurface scenarios and quantify uncertainty before committing to costly field programs. The company says this approach can help explorers move beyond visualizing geology toward risk-weighted decisions across acquisition, drilling, development, and portfolio planning.
That capability is particularly relevant because new discoveries often take many years to advance from initial identification to production. Terra AI says its system can map assets and uncertainty in minutes, giving developers a faster way to evaluate drilling and geophysical strategies. Its geology reasoning agent is intended to work alongside operators to design more precise exploration plans while reducing unnecessary time, cost, and environmental disturbance.
Expansion Across Resource Sectors
While the company has gained traction in mining projects involving copper, gold, rare earth elements, and reservoirs, it is also applying its platform to adjacent subsurface challenges. Enhanced geothermal projects require reliable underground models to understand heat, permeability, and drilling risk, while carbon storage developers need confidence that selected formations can safely and permanently store carbon dioxide. By applying the same uncertainty-focused modeling framework across these markets, Terra AI is targeting a broader role in infrastructure linked to electrification, energy security, and industrial decarbonization.
Company executives and investors framed the funding as a step toward scaling enterprise-grade deployments rather than simply proving the technology in pilots. Chief Executive John Mern said the investment would help Terra AI expand its generative modeling engine and advance subsurface inference tools needed to meet critical mineral demand. Khosla Ventures partner Rajesh Swaminathan said the company is developing an AI-native approach to exploration, while BHP Ventures’ Laurel Buckner highlighted its potential to improve drill targeting and focus capital on higher-value opportunities.
Terra AI’s $20 million Series A reflects a broader shift in how investors and resource companies are approaching exploration technology. As demand grows for copper, rare earth elements, geothermal resources, and secure carbon storage sites, companies are looking for tools that can compress timelines and improve confidence before large capital commitments are made. The next test for Terra AI will be whether its platform can translate early commercial momentum into measurable improvements in discovery, development efficiency, and project economics at scale.