Classical methods, modern tools
We integrate first-principles chemical engineering with data science and analytics, rather than replacing one with the other.
About us
To be one of the most admired R&D organizations.
At RPDS, we blend traditional chemical engineering with advanced data-driven solutions to elevate your process industry operations. We optimize efficiency, enhance safety, and cut costs by integrating classical methods with cutting-edge data science and analytics.
Whether refining existing processes or creating new ones, RPDS delivers tailored solutions that drive results and give you a competitive edge.
Our mission
To develop high-quality products for our customers using modern technology, proficient R&D, and sustainable operations, and to strengthen [...] customers and key stakeholders to experience our growth journey together.
To continuously develop and deliver innovative solutions to our customers through use of advanced technology, remain completely focused [...] long-term relationships with clients through superior service, quality and commitment.
RPDS software is useful for those chemical, energy, biotechnological and metallurgical industries which want to increase profits through [...] for green field projects, for the optimization of capital and operating costs.
Basically, the software provides reliable estimates of design [...] coefficient, heat transfer coefficient, effective interfacial area, etc. for multi-phase reactors and contactors which are widely [...].
Our approach
We integrate first-principles chemical engineering with data science and analytics, rather than replacing one with the other.
We choose model inputs based on process understanding and causal relationships, not statistical correlation alone.
The point is not a single model. The point is a workflow your engineers can rerun, inspect and trust.
Our leadership
Decades of multiphase reactor research, combined with machine learning and software for industry.
Founder
Chemical engineer and nuclear scientist, known for his work on the design of multiphase reactors. Chancellor of the Institute of Chemical Technology (ICT), Mumbai, and former Director of UDCT/ICT (1999–2009).
Co-founder
Data scientist with a PhD in Computer Science from IIT Bombay, focused on turning process data into insight. His published work with Prof. J.B. Joshi applies machine learning to multiphase equipment, predicting gas hold-up and mass transfer in bubble columns and stirred tanks.