A French deeptech startup has secured €22 million in seed funding to tackle one of the most critical supply-chain bottlenecks of the energy transition: the painfully slow, expensive hunt for new mineral deposits. LITHOSQUARE, applying advanced artificial intelligence to sub-surface exploration, aims to slash the time and cost of discovering the lithium, copper, nickel, and other critical metals on which electrification, data centers, and the industrialization of AI all depend.
The funding round underscores the growing alarm over raw-materials supply. Global electrification and the explosive growth of energy-hungry AI infrastructure are driving demand for critical metals to unprecedented levels. Yet traditional mineral exploration remains a high-stakes guessing game: it can take a decade or more to move from a promising geophysical anomaly to a proven reserve, with success rates often below 1%. This fragile pipeline is now seen as a systemic risk to both the green transition and digital sovereignty.
LITHOSQUARE’s thesis takes AI out of the cloud and literally into the ground. Its platform fuses geophysical data, geological models, and satellite imagery to identify high-probability mineralisation zones with a level of speed and precision that traditional methods cannot match. The company says its proprietary algorithms can reduce exploration timelines dramatically while improving discovery rates, effectively transforming the front-end of the mining value chain.
Backers of the seed round include a mix of European venture capital firms and strategic investors focused on climate-tech and resource resilience. The fresh capital will be used to scale LITHOSQUARE’s AI platform, expand its geoscience and engineering teams, and deploy its technology on live exploration projects across multiple jurisdictions.
The announcement comes as policymakers and industrials increasingly view critical-metal independence through a security lens. By compressing the exploration cycle and lowering the barrier to new discoveries, LITHOSQUARE’s approach could help diversify supply away from geopolitically concentrated sources and create a faster, more responsive pipeline for the raw materials that underpin everything from electric vehicles to grid storage and the next wave of AI hardware.