PhysicsX
London-based physics AI startup helping industrial companies design, simulate and optimise complex hardware across aerospace, defence, semiconductors, automotive, energy and data centres.
Europe's most interesting startup stories. Every week.
No spam. Unsubscribe anytime.
Podcast Episode
🎙️ Deep Dive
PhysicsX, Bending Spoons, NewOrbit — $300M industrial AI, Nasdaq IPO and VLEO satellites — Daily News June 8, 2026
Listen to the episodeAbout PhysicsX
PhysicsX develops an AI-native platform for industrial engineering. Its software reduces the time required for complex physics simulations, enabling engineers to explore many more design variants and carry physics insight across the product lifecycle. The $300M Series C led by Temasek at an approximately $2.4B valuation reinforces the thesis that physics AI can become an operating stack for hardware innovation.
The Story
Founded by engineering and physics simulation experts including Jacomo Corbo and Robin Tuluie; full founding year and founder details require verification.
How PhysicsX works
Business Model
B2B enterprise software for industrial engineering, simulation acceleration and AI-powered design workflows.
Revenue Model
Likely enterprise SaaS/licensing and implementation services; details are not public.
Products & Services
Key Products
- Physics AI platform
- Large Physics Models
- AI-native engineering platform
Core Use Cases
- Simulation acceleration
- Hardware design optimisation
- Digital twins
- Engineering productivity
- Industrial design exploration
Market & Clients
Key Customers
Industrial organisations in aerospace & defence, automotive, semiconductors, materials, energy, renewables and data centres.
Geographic Presence
How PhysicsX competes
Competitors
Competitive Advantages
- Physics-domain AI focus
- Deployment across multiple industrial sectors
- Large growth round with strategic industrial investors
- Capability to reduce simulation from hours or days to seconds
How PhysicsX grows
Growth Strategy
Use Series C proceeds to expand globally, deepen platform capabilities and invest in frontier research for larger pre-trained physics AI models.
Distribution Model
Enterprise sales and strategic partnerships with industrial organisations.
Moat (Defensibility)
Physics AI models, industrial deployment data, domain expertise and enterprise integration across engineering workflows.
Regulatory Context
Relevant to defence, aerospace, semiconductor and industrial safety requirements.
Key Risks
- Need to prove accuracy and reliability in safety-critical environments
- Long enterprise procurement cycles
- Competition from incumbent engineering software vendors
- High compute and research costs
Strategic Insights
- The next wave of industrial AI does not replace engineers; it expands their ability to explore physically valid alternatives.
- Data centres, semiconductors, defence and energy create demand for faster and cheaper engineering.
- Large Physics Models may become an infrastructure layer for advanced design and manufacturing.
Funding & Investors
Latest Valuation
Funding Rounds
- 2026 - Series C: $300M
Lead: Temasek
Key Investors
Founding Team
Founders
Key Executives
- Jacomo Corbo - CEO
Key Metrics
Lessons from PhysicsX
- In deeptech markets, value emerges when AI reduces a measurable technical bottleneck.
- Enterprise credibility requires domain physics, not only generative models.
- A major growth round must finance global expansion, product and frontier research together.
Similar Startups
Scope
London-based startup building an AI platform for testing, inspection and certification, helping industrial inspectors capture data, retrieve context and generate reports.
Read AnalysisHIVE
HIVE brings autonomy to existing industrial machines across logistics, production, construction and infrastructure.
Read AnalysisStirlingX
StirlingX helps defence and critical infrastructure customers capture, secure, fuse and turn sensitive data into operational intelligence.
Read Analysis