BeyondMath, a Cambridge, UK-based developer of foundational AI models for physics simulations, has raised $18.5M in seed funding, including a $10M extension led by Cambridge Innovation Capital. The platform trains AI on fundamental laws of physics to deliver engineering-grade multiphysics simulations up to 1,000x faster than traditional CFD and FEA methods. The capital will expand the world's largest foundational physics AI model and support custom enterprise deployments.
Seed Follows Siemens AI Award Win
The timing aligns with growing AI adoption in industrial simulations, highlighted by BeyondMath's third-place finish in the Siemens Industrial AI Awards in May 2025. Partnerships with NVIDIA and AWS underscore hardware optimization for AI-driven physics. BeyondMath's generalized model — requiring no customer-specific retraining — differentiates it from simulation tools needing domain-specific tuning.
Traditional Simulations Drag Design Cycles
Engineering teams in aerospace and automotive rely on CFD and FEA, which demand thousands of compute hours for tasks like full-car aeromaps in Formula 1. Design cycles stretch months due to iterative testing on high-performance clusters. Current solutions limit exploration of novel geometries, constraining innovation in sectors from wind turbines to semiconductors.
Foundational Model Delivers Minute-Scale Sims
BeyondMath's generative physics platform simulates complex multiphysics phenomena — fluid dynamics, heat transfer, structures — using a single foundational model trained on core physics principles. This enables F1 teams to generate full-car aeromaps in minutes versus thousands of CFD hours.
As CEO [Name] noted:
"[We have created the ChatGPT moment for physics.]"
The approach unlocks novel designs inaccessible to conventional methods, with applications in automotive, aerospace, energy, and electronics.
Tier-1 VCs Signal Physics AI Bet
Cambridge Innovation Capital led the $10M extension, joined by UP.Partners, Insight Partners, and Inmotion Ventures. Insight Partners' participation provides growth-stage expertise, while Inmotion Ventures (Ford's fund) validates automotive applications. This mix signals conviction in foundational models disrupting $multi-billion simulation markets.
Multiphysics AI Targets Key Verticals
BeyondMath serves automotive (including F1 for aero/thermal), aerospace (Honeywell), energy (wind turbines, turbomachinery), defense, semiconductors (cooling), construction, telecom antennas, electronics, and data centers. A $19M STRATA project with Honeywell demonstrates enterprise traction. Recent selections for IRCAI and AWS 2025 Compute for Climate Fellowship highlight climate applications.
Enterprise Deployments Follow NVIDIA GTC
BeyondMath plans custom on-prem and private cloud deployments for its waitlisted Generative Physics Platform (studio.generativephysics.ai). Exhibiting at NVIDIA GTC Paris in February 2026 positions it for GPU-accelerated scaling. The $19M Honeywell project and F1 customer validate path to production.