Monolith AI: KTN lays the foundations for Monolith AI’s monumental journey

Posted on: 24/11/2020

Richard Ahlfeld, the founder of Monolith AI, can trace the moment his career changed to a dinner in 2015 arranged by KTN.

In December 2015, Luis Crespo, then a Senior Research Scientist at NASA, was invited over to the UK by KTN’s Uncertainty Quantification and Management (UQ&M) Special Interest Group.  He was to give two talks; one hosted by Professor Montomoli at Imperial College London on ‘Interval Prediction Methods’ and the second a public event outlining the results of NASA’s Langley Uncertainty Quantification Challenge.

Following the talks, Matt Butchers, KTN’s Industrial Maths Knowledge Transfer Manager, arranged a dinner for Luis Crespo and Professor Montomoli to which the latter’s student was invited. Both KTN and Imperial College were aware of the importance of the meeting; it represented the opportunity for a student placement to be secured at NASA.

So, Richard Ahlfeld found himself at dinner with his supervisor and NASA, a dinner he describes as pivotal and where his entrepreneurial career started.  That meeting led to him spending three months at NASA’s Langley Research Centre in the USA working with Dr Crespo on surrogate models for space launch for NASA’s Space Launch System, which will carry humans to Mars in the mid-2030s.

Richard comments: “The first hurdle to overcome was that NASA doesn’t let just anyone work on projects so fundamental to America’s future in space, especially people who aren’t US nationals.  To make sure my work was meaningful, I persuaded NASA to create a ‘toy’ model where I could work with open source data in a “realistic but not real” manner.  That’s a pretty rare event.”

That project eventually resulted in the necessity for a machine learning tool.  Ahlfeld was sure he was onto something but wondered if it was just an academic project and whether it was transferable to industry.  He knew that processes that took him three months at NASA could now be completed in a matter of hours.  KTN once again proved to be the fillip he needed.  He took part in a UQ&M study group and a ‘Visualising to Communicate Uncertainty’ workshop hosted by KTN; other engineers at those events helped him validate the technology concept and confirmed for him that there was a gap in the market.  The opportunity to move from academia to becoming an entrepreneur was there but he knew he needed support to commercialise his solution.

His company, Monolith, was born, and after six months on the Founders Factory Accelerator Programme, he and Monolith have gone from strength to strength.  Ahlfeld is now in the top 10 innovators under 35 list in Germany, his company is now at 35 in the UK’s Top 100 Start-ups list and recognised as one of the most radical start-ups on that list (curated by Startups), Monolith were finalists in the Hottest AI category at the 2020 Europa Awards and one of only 29 companies selected for the UK’s first ever Applied AI growth programme. Along the way he as won an EPSRC Doctoral prize fellowship and a Royal Academy of Engineers Enterprise Fellowship.

Monolith’s machine learning software is built to capture physical relationships in engineering data. It is proving exceptionally attractive to companies such as Siemens, BMW, and Honda and the company is growing rapidly. The company now employs 22 people and has been successful in raising more than £4m in venture capital investment or grant funding.  It has recently announced a Strategic Distribution partnership under which TOYO Corporation will distribute and deploy Monolith’s AI software platform in the Japanese engineering and manufacturing marketplaces.  Richard commented:

We find that companies are literally sitting on billions of dollars’ worth of engineering data.  Our tool helps to unlock that, reducing simulation, testing and costly experimentation.

How did KTN help?

This meteoric rise is a combination of an innovative product meeting a market need, the founder’s entrepreneurial endeavours, Monolith’s attraction as an investment proposition, and KTN’s ability to spot potential and make effective connections.  KTN has helped an academic become a successful entrepreneur using its powerful connections to make positive changes.


Image Credit: NASA/MSFC

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