Meet Deltan Labs: Helping Industry Optimize Materials More Sustainably

How has the process been from being a research to business project to now a startup? 

It has been an exciting process! During the R2B project, we successfully validated our technology with 10 industry pilots. We learnt a lot from talking to our PoC partners and gained a better understanding of industry needs, and how our ML algorithm can solve their pain points. 

The support we received throughout the process has been invaluable. Aalto Startup Center provided workshops, events, and feedback during this journey, helping us get to where we are as a startup. Aalto Innovation Services also made the spinoff process a smooth one. 

Do you have some data to back up your work? 

We completed 10 industry pilots across materials, pulp and paper, semiconductors, polymers and energy. Our ML algorithm optimizes from heterogeneous, spare datasets with 15 – 100 rows (compared to 1,000+ for conventional tools). It optimizes multiple parameters simultaneously instead of one at a time. In pilots, this reduces iterations by up to 70% and cuts development cycles 3 – 5 times. We also learned that many existing tools are quite static and do not support continuous learning as teams iterate the optimisation. This continuous learning is one of the value points we can bring to the industry.  

Could you briefly introduce the team? What made the team jump from academia to startup life? 

We are four co-founders in the team, combining materials science, machine learning and industrial execution. Isaac Miranda leads the company with a PhD in Engineering Physics and deep expertise in materials optimization. Kourosh Mobredi heads engineering, combining advanced materials knowledge with algorithm development. Markus Holmström brings several years of experience commercializing deep tech innovations in industrial sectors. Pamela Ngui drives operations and sustainability, ensuring we translate technical breakthroughs into scalable business. 

The team saw a common problem in the industry, where R&D and production teams waste months developing and optimizing materials and processes. Trial-and-error workflows are slow and expensive. Existing tools are static and require large datasets. Thus, the motivation to create an easy-to-use product that industrial teams could utilize for everyday decision-making. 

What do you expect (or problems that you will face) now that you are in a startup?   

The next phase is about converting strong technical validation into repeatable commercial adoption. We are also working on an on-premise solution, integrating with legacy systems, and proving that the platform fits naturally into recurring industrial workflows. 

We recognize familiar deep-tech startup challenges: earning trust in conservative industries, handling data-security expectations, and differentiating clearly in a competitive market. At the same time, these are also the areas where Deltan Labs believes its explainability, small-data capability, and continuous-learning approach create a real advantage. 

Deltan Labs will join Aalto Startup Center's main accelerator, the Business Generator program, in September this year, joining the community of deep-tech sustainability companies creating a more sustainable future with their inventions.

• More about Deltan Labs: deltanlabs.com
• More about Aalto Startup Center: startupcenter.aalto.fi