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Factory digital twin across a plant network
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Multi-site manufacturingDemo on requestReference scenario

One live view of every plant, before the scrap is made

A factory digital twin links production, energy, maintenance and quality across your plant network. Problems surface in time to act, and the data stays inside each factory.

Request a demo How it works
Status
Demo on request · reference scenario
Data
Stays on site: one binary per plant, on your own hardware
Basis
Anonymised reference platform, reported in production; not a NatusAI customer result
The business problem

Dozens of systems, no view across plants

A global manufacturer runs production, energy, maintenance and quality across dozens of disconnected systems, with data in many languages, analogue processes and silos.

By the time a problem shows up in a report, the scrap is already made and the line is already down.

How it works

Connect the floor, model the plant, act in time

The platform connects machine sensors, manufacturing systems, energy meters, maintenance logs and quality checks into one shared model.

  1. Connect

    Ingest from the plant floor

    Native connectors bring machine and plant data in without extra middleware, on hardware right next to the machines.

  2. Model

    One model of production

    Production, energy, maintenance and quality data from every plant live in one connected model: a production digital twin.

  3. Act

    Predict and optimise

    Machine-learning models forecast failures so maintenance is planned, and live equipment effectiveness shows where to act.

Engineer on site checking live equipment data on a tablet
What leaders get

Fewer surprises on the line

For a COO or head of manufacturing, the value is earlier warning, and decisions based on the whole network rather than one plant’s report.

  • Planned, not reactive, maintenance. Failure forecasts let teams schedule interventions before the line goes down.

  • Effectiveness across the network. Live availability, performance and quality for every plant, with the levers to act on them.

  • Data stays in the factory. One binary per site on your own hardware, so the data stays inside each factory.

Products involved

What it is built with

These roles show how the use case fits the NatusAI architecture. They do not imply that the reference deployment used every product.

  • NatusAI CygnusPlanned v1Data foundation for graph, time, location and search data
  • NatusAI OrionRoadmapApplication platform that turns data capabilities into usable tools
  • NatusAI LyraAvailableInterface components for operational views, maps and dashboards
  • NatusAI AurigaRoadmapAI coordination for assisted analysis
  • NatusAI DracoRoadmapControlled deployment and integration across sites

What you can buy today: a delivery engagement led by our team, built on the engine proven in our client projects, with NatusAI Lyra interfaces. Products marked Roadmap show where the platform is going; we share dates under NDA.

Status: the reference deployment and its reported outcomes belong to an anonymised industrial case on the same engine as our client projects. The anonymised reference platform is reported in production and has received industry recognition. It is not a NatusAI customer result.

Sovereignty, governance and security at NatusAI

For your technical team
  • Native connectors: OPC-UA, MQTT and Kafka in, with no extra middleware.
  • Edge deployment: one binary per site on commodity and ARM hardware, next to the machines. The database runs where the data is.
  • One unified model: production, energy, maintenance and quality from every plant in one graph and one transaction.
  • Predictive maintenance with machine-learning failure forecasts; OEE (availability, performance, quality) computed live across the network.
  • Connector and edge behaviour describe a source capability pattern mapped to planned NatusAI product roles. It is not a verified NatusAI Cygnus release claim.
Demo on request

See the plant-network demonstration

The demonstration shows how an industrial data platform connects production signals with operational decisions. We walk you through it and discuss your plants.

  • Production, energy, maintenance and quality in one view
  • How data stays on site at every plant
Request a demo
Open the preview file (MP4, 0.3 MB)
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Questions

Industrial data operations: questions leaders ask

More answers on deployment, governance and pricing in our FAQ.

Does plant data have to leave the factory?

No. The pattern runs one binary per site on your own hardware, next to the machines, so the data stays inside each factory.

Which machine protocols does the factory digital twin connect to?

OPC-UA, MQTT and Kafka, through native connectors with no extra middleware. This describes a source capability pattern, not a verified NatusAI Cygnus release claim.

Is the industrial reference deployment a NatusAI client result?

No. It belongs to an anonymised industrial case on the same engine as our client projects. The anonymised reference platform is reported in production; it is not a NatusAI customer result.

Talk to our team

Which line would you watch first?

Start with one plant and one recurring problem, such as unplanned stops, energy or scrap. We will scope a first connected view and how to measure it.

  • Start with a scoped discovery phase that ends in a clear go / no-go decision.
  • Bring one real question; we show where AI helps and how we would measure it.
Discuss industrial operations All use cases

Or write to contact@natusai.com

A consultant and a client in a first meeting (illustrative image)