Eight years of real experiments, real batches, and real operational decisions — that is the foundation of our materials informatics system. We are building AI/ML on top of 1,000+ synthesis batches spanning 25 distinct chemistry families, because in physical materials science, diversity of data beats volume. This is what the foundation of an AI-native discovery engine looks like when it is built on real complexity.

Charged molecules are everywhere — from DNA therapeutics to environmental toxins. Yet separating and analyzing them cleanly remains one of analytical chemistry's toughest challenges. Traditional methods like IP-RPLC and IEX force a frustrating trade-off: great separation or great MS detection, never both. Electrochemically Modulated Liquid Chromatography (EMLC) using carbon microbeads, replaces messy chemicals with precise electrical control for cleaner, faster, and more sust