Altrove contacted me to increase the throughput of their in-house material discovery lab. The goal was to increase the speed of data collection for their datasets, which are used to train best in class physics-based AI models. Altrove applies these models to design alternatives to critical materials (like rare-earths and cobalt) 10 times faster than conventional R&D.
To support Altrove best, I relied on my network and partnered with Daniel Salley, a Chemistry PhD who was the head of engineering at Chemify. This partnership ensured the work was informed by my expertise in AI and Robotics, as well as the expertise of an experienced Chemist who has built custom automated platforms.
We conducted a rapid-turnover system-level study of their physical lab operations that uncovered key bottlenecks and needs for operational buffers. We then suggested improvements as a pragmatic mix of simple, custom 3D-printed devices, along with a cost-effective trade-off between full automation and parallelisation. This established a clear path to increase their throughput fivefold within their current lab space, within 1 year.
I drew from my experience as a team-leader of an interdisciplinary research team in the Cronin group, a world-leading AI+Chemistry lab headed by Lee Cronin, whose spin-out Chemify raised a $50M series B to speed up the development of new drugs and medicines by automating the process of designing new molecules.
Altrove recently raised a $10M Seed round to scale their AI-predicted materials from gram-scale to industrial reality. Headquartered in Paris, Altrove has already secured over a dozen partnerships with industry giants across the automotive, energy, and heavy industry sectors.
