ATI Boeing Accelerator Interviews CEO Ben Pellegrini 

Explain Intellegens in one sentence

Intellegens has developed a deep learning platform, Alchemite, to help guide the design and optimisation of new materials based on very sparse and noisy data.

Tell us about the problem you’re solving in aerospace

Intellegens are using ML to help design advanced materials faster than ever before. New materials, particularly in aerospace, require many expensive experiments and certification cycles, Intellegens tools can optimise new materials for multiple target properties and reduce the need for many experimental cycles by around 80%. Example applications include new alloys for high-temperature use, allowing engines to run hotter and therefore more efficiently and new alloys and process for Additive Manufacturing (AM), allowing new components to be printed to the precise shape and more lightweight.

How did you manage the spin-out from the University of Cambridge?

My CTO and Co-founder, Gareth Conduit and his academic group at the University of Cambridge had always been very commercially focused and had undertaken several consultancy projects in the industry. Taking the next step, Gareth developed his ideas with the help of Cambridge Enterprise and a local angel, who then introduced Gareth to me and that’s how Intellegens was created!

Intellegens tools can optimise new materials for multiple target properties and reduce the need for many experimental cycles by around 80%.

Why is now the right time for your company to be doing what you’re doing?

Companies are starting to understand the value of the materials data they hold and as such becoming more organized in managing it. This combined with more accurate computer simulations mean that AI and ML can be used to accelerate future materials design. Our machine learning package, Alchemite, is uniquely positioned to take advantage of the emerging databases and augment them with results from computer simulations in a holistic design tool.

What other industries are you currently working in?

Our USP is the ability to work with very sparse and noisy datasets, a common problem across many industry verticals. Part of Intellegens’ journey has been exploring opportunities in a wide range of domains ranging from consumer electronics, oil and gas, predictive maintenance and autonomous cars. However, we are now focusing ‘industrial formulations’ or industrial ‘recipes’ where there are some ingredients, some treatment processes and resultant, desired, properties. We think this approach can apply to materials, chemicals, and drugs-related problems and we are running several POC projects in with customers in construction, cosmetics, lubricants, batteries, and alloy design.

There are a lot of opportunities out there but it’s not quick or easy to work with big enterprises — having patience and determination to see projects through is critical to getting to the next stage

What are you doing well as a company and where are there opportunities to grow?

The new materials we are proposing to customers are delivering on the promise, with several new materials being experimentally verified and moving into production. Future opportunities to grow are not only in materials but other industries that have a lot of sparse data including chemicals, healthcare, manufacturing, and pharmaceuticals.

Greatest learning from your startup journey so far

There are a lot of opportunities out there but it’s not quick or easy to work with big enterprises — having patience and determination to see projects through is critical to getting to the next stage. Also, getting the right people is hugely important which can be difficult and should not be rushed.

If you weren’t building your startup, what would you be doing?

Another startup!

It comes back to getting the right people in the team that can help support and complement existing skills

What has been your biggest challenge so far and what would your advice be for the future entrepreneurs out there?

I’m not sure there is one specific challenge that could be identified as the biggest, more that there are lots of varied challenges — team, customers, product, technology, legal, sales, marketing, investor management, HR— there is always a new challenge. To help with this it comes back to getting the right people in the team that can help support and complement existing skills.

Any tips for preparing your application to the ATI Boeing Accelerator?

Having a very clear message on how your startup could deliver ROI in aerospace quickly is key. Aerospace is a very slow-moving industry and this accelerator is creating a platform to help change that, the sponsors and accelerator team are passionate about helping startups deliver this, so clearly highlighting cost benefits would make for a very interesting application.

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