Better decision making, powered by Digital Twin Lite

Better decision making, powered by Digital Twin Lite

Unlock the power of risk-free scenario simulation and predictions

Key features

Purpose-built for waste treatment plant management.
Advanced scenario modelling
Gain insights into core operational metrics and their impact by testing various scenarios based on your own real data
Fully customisable
Intuitive drag and drop interface allows anyone to easily recreate, build and configure sites
Cloud-hosted
Access your digital twins and site models from anywhere in the world, and experience faster time to benefit realisation without compromising on security
AI-powered insight
Get future predictions based on past data to help you take proactive action and avoid potential issues and financial risks

How can I easily create digital twins of my sewage treatment plants without in-depth domain or technical knowledge?

Digital Twin Lite provides users with an incredibly easy, seamless and intuitive process for creating and customising their own sewage treatment sites without the need for complex domain and industry knowledge.

Can I manage and compare the performance of multiple digital twins in a central location to take high-level action?

Digital Twin Lite can allow users to create a portfolio of digital twins, representative of their real-world sites, with the added ability to obtain high-level information about the relative performance of plants to enable targeted interventions and investigations on underperforming or non-compliant sites.

How can I simulate plant scenarios to test performance, compliance, and maintenance planning without real-world risks?

Digital Twin Lite's simulation engine provides insights into plant operations and process parameters through end-to-end simulations and in-depth investigations of each process node, unlocking operational efficiencies.

Can I use existing operational data to predict plant performance and benchmark my site's digital twins against it?

Digital Twin Lite can use ML algorithms on real-world site data to benchmark against its virtual counterpart and predict potential performance or compliance issues. The product's simulation capability can then be used to address these issues and enable future planning.

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