Swiss AI startup Giotto.ai is seeking to raise more than $200 million at a valuation exceeding $1 billion, positioning itself as Europe’s latest contender in the race for artificial general intelligence (AGI). The Lausanne-based company has hired investment bank Lazard to lead the fundraising, which will test investor appetite for a new European AI player in a market dominated by well-funded U.S. labs like OpenAI and Anthropic.
What you should know: Giotto.ai plans to use the capital for AI research, building commercial prototypes with enterprise and government clients, and open-sourcing core technology.
- The company was launched in 2017 by CEO Aldo Podesta, who previously worked in sales strategy at Philip Morris, a major tobacco company.
- Giotto has raised CHF 15 million ($19 million) since its founding and sold its medical device compliance product to medtech company RQM+ in 2022.
- The startup now focuses on fundamental research on reasoning models.
The big picture: European AI funding is heating up as the region seeks to cultivate homegrown AI leaders outside the U.S.-China competition and pushes for digital sovereignty.
- Paris-based Mistral AI raised 1.7 billion euros ($2 billion) this month at a valuation exceeding $14 billion, with 1.3 billion euros from Dutch chip equipment maker ASML.
- The fundraising will test whether investors are willing to back new entrants outside Silicon Valley in the crowded frontier model development race.
Competitive landscape: Giotto claims a leading position in the constrained Kaggle ARC-AGI-2 leaderboard with a 25% score and markedly lower costs per task than larger labs.
- ARC-AGI-2 tests a model’s ability to infer rules from limited examples, skills viewed as early signals of general reasoning capability.
- Giotto competes in Kaggle’s fixed-resource track with strict constraints: no internet access, 12-hour time limits, and standard hardware budgets.
- This differs from the unconstrained ARC Prize website used by major labs like OpenAI and Elon Musk’s xAI, where teams can deploy larger models and significantly more compute power.
Why this matters: A higher ARC-AGI score suggests systems can generalize to unfamiliar problems—a capability viewed as a proxy for progress toward more capable, reliable AI and eventual artificial general intelligence.
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