Key Takeaways
- Paris-based Lithosquare has raised about €21.3 million (around 25 million dollars) to accelerate transition-critical mineral discovery using its Geology AI platform.
- The round is co-led by World Fund and Kindred Capital, with participation from daphni, Omnes and OVNI Capital, positioning Lithosquare among Europe’s best-funded mining-tech AI startups.
- Lithosquare’s platform combines foundational AI with subsurface geological models to cut exploration analysis timelines from months to days for copper, lithium, nickel and other critical minerals.
- The funding comes as the world needs more than 1,000 new mineral deposits by 2040 to meet demand, with lithium demand projected to grow over 400 percent and copper roughly 50%.
Quick recap
Paris-based mineral exploration startup Lithosquare has raised approximately €21.3 million in new funding to speed up the discovery of transition-critical minerals using its Geology AI platform.
The round, co-led by climate-focused World Fund and early-stage investor Kindred Capital alongside daphni, Omnes and OVNI Capital, was announced publicly via social posts from World Fund and industry observers. The company says it will use the capital to compress exploration workflows and scale globally as demand for critical raw materials intensifies.
Geology AI to de-risk exploration capital
Lithosquare’s Geology AI platform blends foundational AI models with science-based subsurface geological models to interpret vast volumes of geological, geophysical and remote-sensing data. By automating data processing and target generation, the system aims to let exploration teams focus capital and fieldwork on the most promising copper, lithium, nickel and other critical mineral prospects, reducing both time and uncertainty compared with conventional methods.
According to investors, the platform can shorten analysis cycles from months to days, which can materially change the economics of early-stage exploration portfolios and joint ventures. Lithosquare already works with partners such as Aterian plc, where its AI-led joint venture has delivered eight priority targets across Morocco and Botswana on schedule, demonstrating that its models can translate into concrete drill-ready prospects.
The new €21.3 million injection will likely fund further platform development, including scaling foundational models, expanding the team of geologists and AI engineers, and onboarding more exploration and mining clients seeking to de-risk portfolios in a capital-intensive industry. With investors explicitly framing the company as “critical discovery infrastructure” for the energy transition, the round also signals growing institutional confidence in AI-native workflows for subsurface resources.
Why this matters in today’s minerals race?
Critical minerals like lithium, copper and nickel have become a structural bottleneck for the energy transition, data centres and grid expansion. World Fund cites projections that lithium demand could grow more than 400% by 2040, while copper demand may rise around 50%, putting intense pressure on an exploration system that often takes 7-15 years from idea to discovery.
At the same time, conventional, non-targeted exploration leads to excessive drilling, higher emissions and stranded capital, making AI-guided targeting increasingly attractive to both miners and climate-focused investors. In this context, Lithosquare’s approach of combining deep geological expertise with proprietary AI fits into a broader wave of “geoscience AI” platforms emerging between Europe, North America and Australia.
While majors are building internal data-science teams, nimble startups like Lithosquare are positioning themselves as external infrastructure that can plug into multiple portfolios, effectively selling AI-augmented exploration as a service. Regulatory momentum around domestic supply chains in Europe and North America may further support such platforms, as governments push for faster, more environmentally responsible discovery pipelines.
Competitive landscape
Below is an illustrative comparison between Lithosquare and two similar-scale AI mineral exploration startups, KoBold Metals and Minerva Intelligence, focusing on how their “platform” capabilities would look if expressed in model-style feature terms.
| Feature/Metric | Lithosquare (Geology AI) | Competitor A: KoBold Metals | Competitor B: Minerva Intelligence |
| Core focus | AI-driven critical mineral exploration for energy transition metals. | AI and machine learning for battery metal exploration and development. | AI decision-support for geology and mining risk analysis. |
| Context Window | Large-scale, multi-basin geological and geophysical datasets across countries. | Global multi-asset datasets spanning exploration to development projects. | Regional to deposit-scale datasets focused on knowledge graphs and reasoning. |
| Pricing per 1M Tokens | Project-based or JV-linked fees rather than per-token pricing; economics tied to targets and royalties. | Equity, royalties and project-interest structures, plus service agreements. | SaaS or project-based licensing for mining and consulting clients. |
| Multimodal Support | Integrates geological maps, drill data, geophysics and remote-sensing imagery into unified models. | Combines geological, geochemical, geophysical and operational data streams. | Focused on structured geological data, text reports and semantic reasoning. |
| Agentic Capabilities | Acts as an “AI co-pilot” for exploration teams, proposing targets and work programs. | Embedded in exploration workflows to guide drilling decisions and portfolio allocation. | Provides explainable recommendations on geological risk and interpretation. |
| Stage & geography | Early-growth, Europe-led, expanding globally with fresh €21.3M raise. | Later-stage, globally active with significant backing and assets. | Small to mid-sized, focused on decision intelligence for mining. |
While KoBold Metals likely leads on capital scale and asset ownership, Lithosquare appears more focused on being a flexible AI infrastructure layer for multiple exploration partners, especially in Europe. Minerva, by contrast, remains stronger in explainable geological decision support, while Lithosquare leans into high-throughput targeting and joint-venture economics.
Sci-Tech Today’s Takeaway
In my experience, when specialist investors like World Fund co-lead a €21.3 million round at this stage, it usually signals not just confidence in the tech but in the near-term commercial pipeline as well. I think this is a big deal because AI that directly compresses exploration timelines and capex in critical minerals sits at the intersection of climate, infrastructure and raw-material security, which are all priority themes for institutional capital right now.
I generally prefer business models where AI is embedded into existing high-value workflows, and Lithosquare fits that pattern by augmenting geologists rather than trying to replace them. Overall, this funding looks bullish both for Lithosquare’s growth prospects and for broader adoption of AI-native exploration strategies across the mining value chain.
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