A New Impetus for AI in Engineering

NP Company (NP Co.), a startup positioned at the forefront of AI-native simulation software, has announced the closure of a €6 million pre-seed funding round. The company targets strategic industrial sectors such as aerospace, defense, energy, electronics, data centers, and automotive, promising to revolutionize design and development processes.

The round was led by Partech, with participation from the Peugeot family office and several prominent angel investors. These include well-known figures in the European artificial intelligence landscape, such as Guillaume Lample and Cédric O, co-founders of Mistral AI, Florian Douetteau, founder of Dataiku, and Vincent Luciani, founder and CEO of Artefact. This support from key industry figures underscores the perceived potential in NP Co.'s vision.

NP Company's Technological Innovation

Founded in 2025 by Emmanuel Menier and Matthieu Nastorg, both PhD researchers specializing in AI for simulation at Paris-Saclay University, NP Co. emerged from Inria, the French national research institute that has played a crucial role in the development of several successful European AI companies, including Mistral AI. NP Co.'s technology is based on a new generation of physics simulation powered by transformer models pre-trained on industrial physics data.

By adapting the architecture behind modern Large Language Models (LLM) to physical simulation, NP Co. aims to dramatically accelerate engineering workflows. Unlike traditional simulation software, which can require days or even weeks to resolve a single design iteration, NP Co.'s technology promises to deliver results in seconds while maintaining the same level of fidelity across entire assemblies. The company states it has demonstrated speed improvements of up to 1,000 times on industrial benchmarks and continues to develop the technology for larger-scale assembly simulations.

Context, Implications, and Data Sovereignty

A key differentiator of NP Co.'s approach is its use of pre-trained foundational models. While earlier generations of AI-based simulators required extensive customer-specific training before deployment, NP Co.'s models are designed to deliver value from the moment they are deployed within a customer’s infrastructure. This characteristic is particularly relevant for the target sectors, where data sovereignty, compliance, and direct control over infrastructure are priorities.

For CTOs, DevOps leads, and infrastructure architects evaluating self-hosted versus cloud alternatives for AI/LLM workloads, the ability to deploy pre-trained models directly on-premise reduces complexity and integration time. This approach can significantly impact the Total Cost of Ownership (TCO), minimizing operational costs associated with continuous training and optimization. The ability to explore thousands of designs in the time it used to take to run just one, as highlighted by co-founder and CTO Matthieu Nastorg, opens new frontiers for engineering, enabling faster iterations and greater innovation.

Future Prospects and Impact on Engineering

The newly raised capital will be used to expand NP Co.'s research team and accelerate the development of its foundational simulation models. In the longer term, the company plans to extend its technology toward automated design systems and real-time operational simulators for industrial infrastructure. This vision aligns with the belief of Emmanuel Menier, co-founder and CEO of NP Company, that the next major breakthrough for AI will come from engineering applications rather than conversational systems.

Menier emphasizes how for decades, the bottleneck in industrial design has been the simulation step. By removing this bottleneck, engineers can spend their time solving humanity's most urgent challenges, rather than waiting for a simulation to resolve. This approach not only promises efficiency but also the possibility of a radically different kind of engineering, where innovation is limited only by human creativity, not by computation times.