32x faster R&D
We offer a Modified Bayesian Optimization approach with propietary algorithms that fast-track chemical innovation.
The best part? Our platform is easy-to-use, reaction-agnostic, processes data within seconds, and does not require coding knowledge.
You can access them through our cloud-based platform or in a consulting agreement.
Hear from our customers why working with Sunthetics has made a positive impact:
After a successful retrospective validation, J-Star Research Scientists were able to reach a 64% reduction in experiments for the “optimization” of crystallization conditions using SuntheticsML proprietary technology, compared to traditional statistical design of
SuntheticsML is a useful and easy to use platform, which automatically builds and optimizes machine learning algorithms to guide experimental work towards optimal operation conditions."Dr. Yuriy Abramov Executive Director of Computational Chemistry and Data Science J-Star Research
During the exploration of new synthetic methods, the Sunthetic platform allowed us to rapidly optimize yield and selectivity, and more importantly to determine the relative impact of each parameter. The real asset of the platform relies on 1. Its user-friendliness, 2. The speed of calculation (less than a minute), and 3. The availability and support of the Sunthetic team.
The algorithm took us to sets of reaction conditions we would never have thought worthy of testing – one of which turned out to be the optimum set of conditions!"Prof. Catherine S. J. Cazin Center for Sustainable Chemistry Ghent University
Sunthetics addresses the urgent need for innovative, sustainable, and efficient manufacturing processes in the chemical industry.
What moves us?
The chemical industry is at the heart of 96% of products we use on a daily basis. It is the third largest contributor to carbon dioxide emissions and half of its resources end up in waste streams. The only way to achieve a sustainable future is to re-imagine chemical reactions. Sunthetics' mission is to accelerate that process.