Cloud-Native DCS

One open API connects software and AI above to batch control below

Run your plant as code

Each piece of the plant is an object in one API

A distributed control system (DCS) is the software that drives a batch process from raw materials to finished product. It runs recipes, controls temperatures and flows, opens and closes valves, records every action, and alerts the operator of events.

Cloud-Native DCS does all of this for regulated plants. Every piece of equipment, recipe, running batch, and alarm becomes a declarative API object. Putting a modern AI tool on the plant goes from a year-long integration per site to credentials and a query.

Request a demo
Watch the full sequence (1:18)

The plant runs on cloud-native architecture

Out of the proprietary stack, into standard infrastructure

The plant model runs on Kubernetes, can live in Git as plain text, and is engineered in the browser.

One open API versus a sealed stack. Where the plant model lives decides what can reach it. Two structures, one above the other. Above, Cloud-Native DCS: one open API rail, the plant model as typed objects, with six consumers docking onto it through identical connectors, three built-in (browser editors, audit and electronic signature, the historian) and three your own (standard tooling, Git, AI and analytics), showing that built-in and bring-your-own tools connect the same way and work against the live plant. Below, a traditional DCS: a sealed proprietary stack enclosing the same capabilities (engineering tools, version and audit, and the control model), reachable through the vendor's own applications, with a historian on its edge through which downstream tools read a copy of the data. Cloud-Native DCSone open APIthe plant modeltyped API objectsYour tools dock into the sameopen API as the built-in onesbrowser editorsaudit + e-signaturehistorianstandard toolingGitAI & analyticsbuilt-inyoursTraditional DCSvendor's proprietary stackengineering toolsversion + auditthe control modelreached through the vendor's own appshistorianYour other tools read a copy of the datamonitoring · reporting · AI

What each of these tools gives you

browser editors
Control logic authored in any browser
audit + e-signature
Every change signed, immutable once written
historian
A running record of values, alarms, and state changes
standard tooling
The plant model queried and changes proposed from the command line
Git
The plant model can live under your version control
AI & analytics
Plant access on credentials and a query

Put the plant in Git

The plant's equipment, recipes, and control programs are plain text

See the change flow

Point your AI at the live plant

The plant model is standard API objects, and one open API serves their live values

See the open API

Enforce the approved model

The platform reverts unapproved changes on its own

Watch drift corrected

Author logic in the browser

Any machine with a browser is an engineering workstation

See the editors
Serving tier: API & operator UI replica autoscale Control tier: edge controllers controller-1 + controller

Elastic where it's safe, deterministic where it must be

The API and operator screens scale out on load, while one writer at a time drives each piece of equipment

See how it scales
Operator HMI Engineering Quality & data one plant model

Give every team one model

Operations, engineering, and quality work from the same live API objects

See the shared model
Compare it against DeltaV, PCS 7, PlantPAx, and Experion, delta by delta →

One system drives the batch and writes its record

The compliance posture spans regulations, industry standards, and guidance

Read the full compliance posture → Start a conversation →