Your partner in production optimization and digital twins.
Your plant drifts. Your model shouldn’t.
Live, self-learning digital twins that optimize in real time — simple to use, understand, and maintain.
Physics Where It Counts · ML Where It Helps◆ AspenTech Independent Solution Provider (ISP) · Presented at AspenTech Optimize 2026
From the wellhead to refined products
Follow the hydrocarbon through the plant — and see the digital-twin solution that plugs in at every stage.
What makes our twins different: they're built from first principles (equation-oriented models of the real process), they self-learn (re-calibrating to live plant data every cycle), and they run closed-loop (sending optimized targets back to the plant continuously).
Not sure where to start? We scope a single-unit pilot anywhere along the chain.
Live installations, worldwide
The full network on one map — live installations worldwide. Filter by fleet.
India Region
8 sites · incl. HQMiddle East Region
6 client sitesOne model. Three jobs. Zero decay.
Built on equation-oriented Aspen HYSYS — the modelling approach that makes plant-wide optimization tractable. The twin runs an automated 20–30 minute cycle: reconcile, calibrate, optimize, publish — continuously.
- Ingest — historian data (IP.21 / PI) validated and reconciled automatically.
- Calibrate — self-learning reconciliation model configured with an innovative
method that re-tunes parameters to the current plant state.Rolling-Window Modal Standard Deviation (RWMSD)Rolling-Window Modal Standard Deviation (RWMSD) — a short-term variability metric derived from the modal value of a sliding-window standard deviation distribution, giving a stable, outlier-resistant estimate for each tag.
- Optimize — the EO model finds the most profitable operating point within constraints.
- Publish — targets and KPIs delivered to dashboards and APC every cycle.
- What-if case studies — run scenario studies on the calibrated twin to evaluate feed, operating, or design changes before applying them in the plant.
Model acceptance: Material balance: as good as client plant data · Uptime ≥90% · Temperature, Flow: as per RWMSD
Data & visualize: Data Historian · Dashboard technology of client’s choice
Industries we serve
Decades of frontline process expertise
Dr. Hiren Shethna
Founder & Optimization Lead- M.Tech IIT Bombay · PhD University of Manchester
- 26 years at AspenTech and Saudi Aramco
- Implemented 25+ digital twin models worldwide
Dr. Karuna Potdar
Simulation & Modelling Lead- B.Chem.Eng + PhD, ICT Mumbai
- 32 years at Reliance Industries
- Led RIL's simulation & modelling team
- 15+ plant models deployed across RIL
Shailesh Sakarkar
Training & Simulation Lead- B.Tech, Laxmi Narayan Institute, Nagpur
- 30 years in the process industry
- 80+ simulation training programs delivered globally
CDU Digital Twin Built with Equation-Oriented Modelling in Aspen HYSYS and Custom Modeling Technology Helps Refinery Improve Margins
Co-authored with AspenTech.
Development of a High-Fidelity FCC Riser Model Through ACM Integration for INDMAX Technology
Co-authored with IOCL R&D Centre Faridabad and AspenTech — a proprietary 27-lump kinetic model validated against commercial plant data.
Technology partners we build on
We deliver on best-in-class process technology, working alongside leading software and equipment specialists.
AspenTech
Independent Solution Provider (ISP)Our digital twins are built on the Aspen suite — Aspen Plus, Aspen HYSYS, Aspen Custom Modeler (ACM), and Aspen Online — delivered as an AspenTech Independent Solution Provider.
Visit aspentech.com ↗MySep
Separation Technology PartnerRigorous gas–liquid separator design and rating, paired with our process simulation for reliable separation-system performance.
Visit mysep.com ↗Knowledge sharing
Talk to us
Unit type, the problem, and whether plant data or a model already exists — three lines are enough to start.
Start small
We can scope a single-unit pilot of the digital twin to demonstrate value before any wider rollout — with defined acceptance criteria from day one.