After years of research at world-leading universities (including Cambridge, Stanford, and Imperial College) and collaboration projects with some of the world鈥檚 most advanced engineering companies (including NASA, Rolls-Royce and Airbus) Monolith was born.
Our AI platform utilises the latest in machine learning, to help design and engineering teams significantly improve the product development process.
How did you come up with the idea for the company?
Monolith AI was founded from my PhD at Imperial College London and my research work on surrogate models of space launches for NASA鈥檚 Space Launch System (which will carry humans to Mars in the mid-2030s).
I have always wanted to build world-transforming tech with the vision behind Monolith being JARVIS from Iron Man, the ultimate assistant for engineers – imagine how quickly we could develop new products with that kind of help!
More from Interviews
- A Chat With Madhu Nadig, Co-Founder & CTO Of Flagright And FinTech50 2026 Judge
- A Chat With Piero Pavone, CEO Of Preciso On How Native Advertising Is Shaping A More Sustainable Future
- Efficient Referrals: Meet Kirsty Sharman, Founder Of Referral Factory
- A Chat With Jo茫o Moura, CEO And Co-Founder, On Transaction Risk Platform: Fraudio
- A Chat With Michael J Bannach, Founder & President, Stealth Technology Group On How Employees Leak Company Secrets Into Chatbots 鈥� And What Safe, Approved AI Should Look Like
- A Conversation With Allister Frost, Future-Ready Mindset Author and Speaker, On How AI Panic Is Pushing Brits Into Rushed Career Swaps That Could Prove Costly
- Interview With Yuliya Barabash, Founder Of SBSB Fintech Lawyers On Where Crypto Companies Actually Win in 2026
- A Chat With Avion Gray (CEO) And Samantha Rosenberg (COO), Co-Founders Of Belong On Wealth Building
How has the company evolved during the pandemic?
The pandemic lockdown accelerated the steady growth of virtual and cloud engineering. Some of Monolith鈥檚 users are engineers at Kistler.
Testing new design performance in-person generally requires multiple people in a shared space. Therefore, throughout the global pandemic, these kinds of tests have either been impossible (depending on the extent of local restrictions) or meant risking your health. With Monolith, however, the engineers at Kistler can use data from previous tests they conducted and accurately predict what would happen this time.
We鈥檝e also introduced a new teams feature – just like with Zoom or Miro – allowing different engineering teams to share data and dashboards and work together more collaboratively.
What can we hope to see from Monolith in the future?
Similar to how Google Deepmind delivered a breakthrough in protein folding, we want to deliver breakthroughs in engineering and sustainability. We鈥檝e already started working with packaging manufacturers and retailers to create more sustainable products without compromising the customer experience. We are also currently focussing on larger projects, such as helping to develop hydrogen-powered aircrafts.
