Solutions · IT & data platform
A governed source, not exports of exports.
Production data with a documented model, real access control and a delivery record, so analytics, reporting and AI work from something you can stand behind in an audit.
- Provides
- A modelled namespace with units, types and quality
- Controls
- Role and namespace-path permissions, including for AI access
- Deploys
- Inside your perimeter, with Docker or Kubernetes
Who sees what follows the plant model.
Roles and namespace-path permissions decide what each person, system and AI assistant can read, and every change is in the audit trail.
The shift
What actually changes.
How it works today
- Plant data arrives through scripts your team cannot see
- Access is a shared database credential
- A renamed tag breaks a downstream model without warning
- Nobody can trace a figure back to the machine that produced it
With Proxus
- One governed path, documented and owned
- Roles and namespace-path permissions for people, services and AI
- Changes to the model are recorded in the audit trail; a change is visible
- Operational logs per gateway and an audit trail of configuration changes
How it plays out
A typical sequence, step by step.
An illustrative sequence, not a customer story: written to show the shape of the work rather than to claim a result. Your equipment, sites and systems decide the detail.
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Review
Security asks its questions
Transport, credentials, access model, audit trail and deployment topology are answered before the pilot, not after procurement.
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Design
Build against the model
Your team reads a documented namespace with units, types and quality instead of reverse-engineering an export.
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Operate
Grant scoped access
A team, a supplier or an AI assistant receives exactly the branch it should see, and nothing else.
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Audit
Explain a number
A questioned figure is checked against the gateway’s operational logs and the audit trail of configuration changes.
What Proxus does here
The working parts behind it.
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Documented model
A hierarchy and signal definitions your team can design against.
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Access control
Users, roles and object-level permissions across data, screens and APIs.
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Programmatic access
REST and messaging interfaces, with unlimited API calls in every package.
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Governed AI access
An MCP interface so assistants work with production data under their user’s own permissions, with deletes blocked.
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Runs in your estate
Containers on your infrastructure, on-premises, private cloud or air-gapped.
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Evidence trail
Collection, transformation and delivery history behind every value.
Deployment scope
What a first deployment involves.
- You deploy
- Containers on your own infrastructure, on-premises or private cloud
- You govern
- Users, roles and object-level permissions, including namespace paths
- You consume
- REST, messaging and governed AI access from the same model
- You audit
- Pipeline revisions, the configuration audit trail and operational logs per gateway
What this enables
- Replace shadow pipelines with a source you can audit
- Apply one access model to people, integrations and AI clients
- Build against a schema that changes deliberately and visibly
- Keep production data inside your own estate
In the product
One namespace from enterprise to tag, with live values
Signals carry units, data types and quality, and changes to the structure are recorded in the audit trail, so a rename is a visible change rather than a broken downstream job.
Local product environment with simulated data.
Proven in production
Governed, documented and audited in production.
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Manufacturing
Digital factory data management
MEXT Digital Factory
Read the case study -
Mining & energy
Mining, fleet and solar on one platform
Kaltun Mining
Ask us about this deployment -
Energy
Grid monitoring at the edge
CK Enerji
Ask us about this deployment -
Manufacturing
Unified Namespace with Oracle ERP
Pilenpak
Ask us about this deployment
Questions
What teams ask before starting.
- How does this fit next to our existing data platform?
- It sits on the OT side of the boundary and feeds yours. Proxus handles collection, modelling and governed delivery; your platform keeps doing analytics and storage the way it already does.
- What does access control look like?
- Users, roles and object-level permissions, including permissions on namespace paths, applied identically to people, integrations and AI clients.
- Can we deploy it on our own Kubernetes?
- Yes. Containers, on your infrastructure, on-premises or in private cloud, with a documented deployment path.
- How do we audit where a number came from?
- Operational logs are kept per gateway, configuration changes are recorded in the audit trail, and pipelines keep revisions you can compare. Together they show what each gateway did and what changed in its configuration.
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.
- 01
Scoping call
Equipment, protocols, sites and the systems the data has to reach.
- 02
Technical walkthrough
A working demo against a scenario that resembles your plant, not a generic tour.
- 03
Pilot plan
A defined first line or site, with the deployment and security questions answered up front.
- 04
Roll-out
The same templates bring the next lines and sites online.
Tell us about your plant
A Proxus engineer replies within one working day.
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