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Proxus 2.0.0 Proxus 2.0: the largest release in Proxus history Release notes
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Solutions

The same data layer, pointed at the problem in front of you.

Most plants do not start with a platform strategy. They start with one line that has to report properly, or one system that keeps going hungry. Proxus is built to start there and still hold up at the twentieth site.

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Starts with
One line, one protocol and one system that needs the data
Works with
Brownfield plants, mixed vendors and equipment that cannot be replaced
Scales to
Multi-site groups running the same namespace and templates
Built in
66 protocols · 18 destination systems · Keeps recording when the network drops

By outcome

What teams come to us for.

OT/IT data integration

One governed path instead of a wire per system.

Every system that wants plant data gets its own driver, script or gateway, and every one of them has to be maintained by someone who understands both ends.

  • One source definition per machine, reused by every consumer
  • Modelled signals with units, scaling and asset context
  • Delivery to databases, brokers, cloud services and business systems from the same pipeline
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Machine & OEE visibility

Line performance from real signals, not a clipboard.

Availability, performance and quality figures arrive late, get typed in by hand, and nobody can trace a number back to the machine that produced it.

  • Cycle counts, states and downtime reasons collected directly from controllers
  • The same calculation applied identically on every line and every site
  • Operational dashboards for the floor, scheduled reports for management
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Condition monitoring

Catch the drift before it becomes a stoppage.

Vibration, temperature and current data exist somewhere, but nothing evaluates them until after the failure has been written up.

  • Statistical anomaly detection running on live streams at the edge
  • Rules and alarms with the context needed to act, not just a red light
  • History kept at full resolution for the analysis that follows
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Cloud & warehouse feeds

Feed the data platform without gaps or bespoke pipelines.

Cloud analytics projects stall on ingestion: brittle exports, missing periods after every outage, and no agreement on what a field means.

  • Buffered delivery at the edge, forwarded when the link returns
  • A stable, documented namespace the data team can build on
  • Azure Data Lake Storage Gen2, ClickHouse, Kafka and the AWS and Azure IoT services as targets, each with its own strategy
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Four teams, one source of truth.

How the platform works

Where it fits

Brownfield plants, mixed vendors, real constraints.

All solutions

Discrete manufacturing

Cycle times, downtime reasons and quality signals from presses, CNCs and assembly lines, modelled per line and comparable across plants.

Process & utilities

Continuous measurements, alarms and consumption data collected from SCADA, meters and controllers without new field hardware.

Multi-site groups

A namespace and rollout pattern that survives the second, fifth and twentieth site, including the ones with different equipment vendors.

Proven in production

Started as one line, in a real plant.

All deployments

Your data, your infrastructure, your rules.

Deployment & security

  • Inside your perimeter

    On-premises, private cloud or air-gapped. Plant data does not have to leave your network.

  • Role-based access

    Users, roles and object-level permissions across configuration, live data, screens and APIs.

  • Encrypted transport

    TLS on every link: edge to hub, the hub’s own services, the built-in MQTT broker and outbound integrations, with certificates from the built-in CA or your corporate CA.

  • Auditable

    Configuration changes are recorded in the audit trail, and pipelines keep revisions you can compare.

Next step

Start with one line, not a programme.

Pick the line that causes the most arguments about numbers. We will scope what it takes to make that one trustworthy, and what the second and tenth would cost in effort.

  1. 01

    Scoping call

    Equipment, protocols, sites and the systems the data has to reach.

  2. 02

    Technical walkthrough

    A working demo against a scenario that resembles your plant, not a generic tour.

  3. 03

    Pilot plan

    A defined first line or site, with the deployment and security questions answered up front.

  4. 04

    Roll-out

    The same templates bring the next lines and sites online.

Tell us about your plant

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