Manufacturers are joining operational technology on the plant floor to IT systems that were never designed to meet it. We help you integrate the two, put plant data to work and catch quality problems while they are still cheap to fix.
The question we hear most
Plant data has been valuable for years, and stuck for just as long: locked in historians, PLCs and spreadsheets on the floor, owned by engineers whose first duty is to keep the line running. Every connection to the business looks like a new risk to them, and often it is.
We connect the plant through layers control engineers recognise — ISA-95 levels, OPC UA, segmented networks — so data moves up without anything reaching down. Then we put it to work where a person stays in charge: early warnings on quality and equipment health, and assistants that know the manuals.
The shifts changing what good delivery looks like here, and what each one asks of the teams doing the work.
Plant data is reaching the business through OPC UA, MQTT and ISA-95 architectures, after years locked in historians.
What it means for deliveryConnectivity has to come with segmentation, because the control network is not an IT network.
NIS2 covers many manufacturers, and the Cyber Resilience Act brings security and reporting duties to products with digital elements.
What it means for deliverySecurity evidence is now needed for plant systems and for the products leaving them.
Inline sensors and machine vision make it possible to catch defects at the station rather than at final inspection.
What it means for deliveryModels on the line need validation and monitoring like any other production equipment.
Experienced technicians are leaving faster than their knowledge is written down.
What it means for deliveryAssistants grounded in manuals and maintenance history keep that knowledge in use, with a person confirming every action.
The pressures differ inside an industry too. These are the parts of it our teams work in, and what sets each one apart.
Engineered products with long service lives and connected after-sales.
Continuous operations where stability, safety and batch records come first.
High-mix, high-precision lines with traceability down to the component.
High-volume lines with tight quality, hygiene and labelling rules.
Energy-intensive plants where small process gains are worth a great deal.
Many customers’ products on shared lines, with each customer’s data kept separate.
Each offering runs on its own or as part of a wider programme, and draws on the AI services, consulting practices and products listed with it.
Plant data moved into the business through ISA-95 layers and OPC UA, without opening a path back into the control network.
Anomaly detection and process analytics that warn about quality and equipment health while a problem is still cheap to fix.
Maintenance assistants and visual inspection that run on site, with a person confirming exceptions.
Changes to MES, ERP and line software planned around the production schedule, tested properly and rolled out with a way back.
We do not certify compliance — your auditors and assessors do. We make sure the evidence each framework asks for is produced by the delivery process itself.
Common first engagements in this sector. Most begin with a two-week, fixed-price discovery that leaves you with a costed plan whatever you decide next.
Yes. Super AI Local System is built for that: we design, rack and tune model infrastructure on your own hardware, so it keeps working whether or not the plant has a link out.
Changes are planned around the production schedule and rolled out in increments, each with a rollback path, so a problem costs minutes rather than a shift.
No. We integrate with the systems you already run and add the traceability, automation and data layer around them.
Not if it is designed properly. We follow the ISA/IEC 62443 approach of zones and conduits, keep data flowing outwards through controlled points, and agree every connection with your control engineers before it is made.
The EU’s NIS2 Directive extended cybersecurity duties to thousands of organisations in manufacturing, transport, health, digital services and more. Most of its ten minimum measures are things engineering teams build and run.
How to replace a system the business runs on one piece at a time, behind an interface that lets everything else keep calling the same address.
Tell us the constraint and the systems behind it. We will put an engineer who has worked with both on the call, not the nearest salesperson.
What the first call covers
