Arlequin AI has raised €28 million in Series A funding to accelerate the development of a new AI architecture based on topological neural networks (TNN*) and expand the international deployment of its technology.
The round is backed exclusively by European investors and co-led by redalpine and OTB Ventures, alongside Bpifrance’s Defence Innovation Fund. Existing investors Vsquared Ventures and 10x Founders are increasing their stakes and Xavier Niel and ZEBOX are joining the round. As the company grows, Arlequin’s technology is already being used by governments and large organizations across Western and Eastern Europe.
Founded in Paris in 2024 by Hugo Micheron, PhD, a specialist in jihadism and geopolitical instability, and Antoine Jardin, a former CNRS research engineer in data science and human behaviour, Arlequin is developing AI for environments where governments and businesses need to make consequential decisions from large, fragmented datasets and where results must remain grounded in underlying evidence.
The company has already built and implemented an easy-to-deploy and scalable platform that analyses relationships across heterogeneous data, from documents and transactions to video and operational information. The new funding will accelerate Arlequin’s next technological step: proprietary models based on topological neural networks, designed to learn from the structure and relationships within data and capture complex, multi-way interactions at scale.
This represents a different architectural path from the one that has dominated the recent development of AI. While large language models have transformed language and content generation, Arlequin is developing models aimed at understanding the structures and dynamics hidden across millions of interconnected data points.
Today, another revolution is taking shape: the development of new AI systems capable of understanding highly complex dynamics hidden within millions of data points. At a time when we are overwhelmed by information, we need to regain control. If AI and algorithms can be used for destructive purposes, we also need algorithms that provide greater transparency and give us greater control over the environment in which we now operate. At a time when Europe’s technological independence is more important than ever, this funding gives us the means to pursue this European ambition.
Topological neural networks are designed to learn not only from individual data points, but from how data is connected, including relationships involving multiple elements at once. Arlequin is developing the architecture to analyse increasingly large and intricate systems while retaining the ability to trace results back to their source.
For example, in a counterterrorism investigation, Arlequin’s platform can analyse millions of data points across multiple seized devices to identify connections between people, locations, communications and events. TNN-based models are intended to extend that capability to relationships and dynamics that become increasingly difficult to identify as datasets grow in scale and complexity.
The same approach is applicable across security and defence, criminal, fraud and money laundering investigations, information integrity, cybersecurity and AI system safety and security — all areas where estimations and predictions are not enough and the evidence behind each result matters.
We believe the next advances in AI will come from fundamentally different architectures, not simply from making models larger and feeding them more data and energy. LLMs have transformed language and content generation, while world models have extraordinary potential for physical AI. With Arlequin’s topological neural networks, we are opening a new field of artificial intelligence for problems that existing architectures are not designed to solve efficiently.
Arlequin is also designing its TNN architecture to require significantly less compute, reducing reliance on the energy, advanced semiconductors and computing infrastructure that increasingly constrain the development of large AI systems.
Development of the new architecture is supported by collaborations with research teams at INRIA, CNRS and Max Planck Institute, as well as at the Universities of Oxford, Cornell, Princeton and UC Santa Barbara.
A different path for European AI
Arlequin’s approach opens a different opportunity for Europe in AI: competing not only by developing European versions of existing technologies, but by originating new architectures and opening new fields of AI. This innovative approach has led to Arlequin’s technology already being deployed with governments and large organisations across Western and Eastern Europe.
The funding will enable Arlequin to expand the international team developing and training its proprietary models and accelerate commercial deployment across Europe and worldwide. The company has opened offices in London and Berlin and plans to establish an AI lab in Silicon Valley in the coming months.
From day one, Hugo and Antoine impressed us with their exceptional founder-market fit, deep technical edge and relentless drive to solve a critical problem. Arlequin is building a truly differentiated, fully productized sovereign tech platform for safety and security in Europe and beyond, and we are convinced this exceptional team has what it takes to build a category-defining company in a market worth trillions.
Founded in Paris in 2024 by Hugo Micheron and Antoine Jardin, Arlequin AI is a European deeptech company developing proprietary AI models and an analytics platform for critical decision-making by governments and large organisations. Its technology is designed to analyse relationships across large volumes of complex, heterogeneous data and deliver traceable, explainable and auditable results.
Arlequin’s technology is deployed across security and defence, criminal and terrorist network investigations, fraud and money laundering, judicial investigations, information integrity, cybersecurity and AI system security, and is active across four European countries.
AI sovereignty is not only about where models are built or data is hosted. It is about having control over the technologies that increasingly underpin our most critical decisions. Europe needs AI systems it can own, understand and trust. Arlequin is building a fundamentally different paradigm of AI, designed to uncover relationships in complex data without predefined ontologies, bias or hallucination, while keeping results traceable and verifiable. This is critical not only for governments, but also for enterprises where reliability is non-negotiable. We are proud to co-lead this round and excited to back Hugo, Antoine and the Arlequin team as they enter their next phase of growth.
Headquartered in Paris, with offices in London and Berlin, Arlequin has around 50 employees, including 35 engineers and 15 PhDs, researchers and data scientists, and will open an AI lab in Silicon Valley by the end of 2026.
Arlequin’s ambition is to build a globally competitive European AI company by developing architectures that offer an alternative to those emerging from the United States and China.
Most of the capital in AI right now is chasing the same architecture and hoping scale solves everything. Arlequin is pursuing a genuinely different architecture: developing topological neural networks as a distinct architectural approach, rather than relying solely on larger models and more compute. What sets the company apart is that this research is the direct engine for a product that is already being used by governments and enterprises, a combination of fundamental science and commercial traction that remains rare in Europe.
