Make the invisible visible.
Bring energy, asset and process behavior into a common operating context.
DigiTwin connects industrial assets, existing systems and operational data into one intelligence layer so teams can monitor what is happening, predict what is changing, optimize what matters and scale with confidence.
A dashboard can display data. DigiTwin is designed to connect the physical operation, existing systems, models, AI and decisions so the plant can move from visibility to action.
DigiTwin is designed as a non-disruptive intelligence layer. Existing plant investments remain useful while missing connectivity, context and intelligence are added in practical stages.
See the connectivity layer ↘DigiGateway provides a practical route to asset-level data where direct integrations are limited. Where useful data already exists, DigiTwin can also work with available APIs, files, feeds and databases.
Energy behavior becomes more useful when it is understood alongside asset state, production demand and operating conditions.
Start with the strongest operational problem and the data you already have. Each stage can create value before the next one begins.
Build a reliable energy baseline and bring utility consumption into one operational view.
The platform grows with the maturity of the operation, from connected visibility to control-ready intelligence.
Bring energy, asset and process behavior into a common operating context.
Detect patterns, deterioration and future operating windows before they become downtime or loss.
Compare actual behavior with stronger operating patterns and identify the actions that improve performance.
Extend proven models across assets, lines, sites and enterprise decision layers.
Connect utility demand to asset state, process load and operating conditions so energy performance becomes actionable.
DigiTwin brings plant signals, operating context and improvement opportunities into a decision interface built for action rather than reporting alone.
EMS monitoring, electrical optimization and prediction for energy-intensive operations.
Health scoring, anomaly detection, early warning and maintenance decision support.
Process monitoring, bottleneck visibility, optimization and predictive control.
Operator visibility, exception handling and plant-level decision dashboards.
Connect output, operating state, constraints and energy to improve plant performance.
Scale connected models, AI and decision workflows across assets, processes and sites.
Every pilot should make a business lever visible, measurable and ready to scale.
Annual savings opportunity identified while maintaining the expected condenser delta-T operating range.
Discuss a similar use case ↗Identified no-hardware savings opportunity using process telemetry, energy data and operating context.
Explore energy intelligence ↗Industrial control deployment connecting real-time process context with optimized setpoint actions.
Explore predictive control ↗Concise answers for manufacturing leaders, technical evaluators and search systems, with deeper context available throughout the page.
DigiTwin is Digi I4.0's proprietary industrial Digital Twin platform. It connects assets, existing systems, operational data, models and AI into a scalable intelligence layer for monitoring, prediction, optimization and decision support.
Digital Twin is the broader industrial concept of representing and understanding a physical asset, process or operation digitally. DigiTwin is Digi I4.0's platform and maturity pathway for building that capability in practical stages.
DigiGateway is Digi I4.0's industrial connectivity layer for collecting asset-level data where direct integrations are limited. DigiTwin can also use existing APIs, databases, files and available data feeds.
No. DigiTwin is designed to work around existing plant investments. The preferred approach is to integrate what already works and add only the missing connectivity, context and intelligence layers.
A manufacturer can begin with the operational problem where value and data readiness are strongest, such as energy monitoring, asset health, process monitoring, predictive maintenance or optimization.
DigiTwin uses a portable Kubernetes-based architecture, modular APIs and edge-compatible models, allowing deployment patterns to be shaped around customer infrastructure and latency requirements.
Not always. If useful operational data already exists in PLCs, SCADA, EMS, MES, databases, files, APIs or other available feeds, DigiTwin can use those sources. DigiGateway is added where asset-level connectivity is missing or insufficient.
Yes. Digi I4.0's preferred approach is to begin with one measurable operational problem, connect the required data, establish a baseline, prove value and then expand toward broader DigiTwin maturity.
DigiTwin can begin with alerts and human-validated recommendations. Where safety, process validation and operating maturity allow it, edge-compatible models and control logic can support progressively more automated or closed-loop use cases.
DigiTwin can support operators, maintenance teams, energy teams, plant heads, operations leaders, digital and IT teams, and CxO stakeholders through role-appropriate operational and business views.
Bring us the recurring loss, risk or operational blind spot. We will help identify the most practical DigiTwin starting point, the data required and the value that should be proven first.