Mechanistic AI - Smarter Digital Twins

Digital twins offer numerous benefits but are costly to develop. Developing one typically requires an expensive high-fidelity simulator and significant amount of time to adapt it to the process data. Yet, such an approach will only result in a solution which can only be run offline.

In contrast, Mechanistic AI based digital twin is developed in a fraction of time achieving ROI in only 1-2 months. MAI - digital twin is run online to fully monitor the process state and to generate predictions in real-time. MAI-DT replaces lab and analyzer samples with online estimates, it helps operators to better evaluate results of their actions in case of processes with slow dynamics and or delays, it assists with maintenance by indicating exactly the faulty parts of the process. As a result, MAI-DT leads to operational costs savings of up to 20 %.


MAI enables efficient control of processes with lacking or malfunctioning instrumentation as well as serves as an engine for predictive maintenance.

Mechanistic AI predictions are significantly more accurate compared to any other method (e.g., seq2seq-LSTM) which typically require 50X more data to even come close to MAI accuracy.