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Supply chain & industry ยท Middle East

The machine data exists. It just never reaches the people making decisions.

Production runs on the floor. Reporting runs on a spreadsheet assembled the following morning.

14 of 20

manufacturing industry groups saw labour productivity decline over the latest published year.

Source: BLS: Productivity and Costs by Industry, Manufacturing and Mining

In the Gulf

This is what it actually runs on here.

Platforms in this market

  • SAP
  • Oracle ERP
  • MES platforms
  • Siemens and ABB control systems

Rules that apply here

  • ESMA and SASO conformity
  • In-Country Value programmes
  • ADNOC vendor standards

We read the rule before the call. It is the cheapest way to prove we did the work.

What is happening

The machine already said it. The person who needed to hear it was elsewhere.

OEE is calculated after the shift, not during it

By the time downtime is visible in a report, the shift is over and the cause is a memory.

Quality data lives where nobody analyses it

Inspection results in one system, scrap in another, customer complaints in a third. The link between them is a person.

Maintenance is reactive because the signal is invisible

Sensors exist on newer lines. The data does not reach anyone before the failure does.

Traceability is a fire drill

When a customer asks which batches contained a suspect lot, the answer takes days and a lot of manual searching.

However hard, whatever it is

Machine data is one example. Bring the one on the board this quarter.

We wrote this about the shop floor seeing what the line already knows. If yours is quality, changeover or a supplier nobody can measure, same job.

  1. 01

    We sit with you

    Days where the work happens, not a workshop in a meeting room. We watch the job get done and write down the shortcuts nobody wrote down.

  2. 02

    We read everything

    Your data, your rules, your vendors and their documentation, and the published research on your sector. We report what is actually in there.

  3. 03

    We break it to first principles

    Not which tool fixes this. What is actually causing it, taken apart until we reach the piece that cannot be divided further.

  4. 04

    Then we build

    Weeks, not quarters. By this point we are not guessing what to build, and guessing is the thing that makes projects long.

Where we sit

Your ERP stays. The PLCs stay. We build what the shop floor sees.

4

What you get

  • Live Line performance visible while the shift is running
  • Traced Batch genealogy answerable in minutes
  • Predicted Maintenance triggered by condition, not calendar
3

Built new for you — none of this exists in your stack today

  • A sensor and enclosure we build when the machine has no port
  • A line screen that gives an operator the one next thing
  • A shift handover that writes itself from the run data
2
The plant-signal layer Reads your machines. Sends no command to any line. Connectors, one agreed meaning per field, and a model reading what no field holds. Accuracy measured on your own records.
1
  • SAP
  • Oracle ERP
  • MES platforms
  • Siemens and ABB control systems

What you already run — unchanged, and still yours

If the machine shows it, we can read it. If it has no port, we build one. PLC tags, OPC-UA, a panel meter with nothing but a display. And where there is nothing, a sensor we make.

  • No API
  • No documentation
  • A terminal from 1994
  • It arrives as paper
  • The vendor said no
  • It reports nothing

Not a list of limits. Name yours on the call.

And once we can reach it, a model can read it. Most of the value here is in the sources nobody ever structured — the note, the letter, the screen.

Intelligence, plumbed in

A shift log and a fault code describe the same event. Now they join.

The build is a machine connector, one fault vocabulary across lines, and a test set of failures you have already had.

How we make AI survive real data
  • Connectors
  • A semantic layer
  • Evals you can check

What changes

Judge us on this, not on what we built.

Live

Line performance visible while the shift is running

Downtime, cycle time and scrap as they happen, attributed to line, shift and cause.

Traced

Batch genealogy answerable in minutes

Raw lot to finished unit to customer shipment, queryable rather than reconstructed.

Predicted

Maintenance triggered by condition, not calendar

Using the sensor data already being generated and currently discarded.

Who this is for

The people who feel this first

  • Plant Manager
  • Operations Director
  • Quality Head
  • Maintenance Manager
  • Supply Chain Director

Straight answers

The questions you would ask on the call

  • Our machines are old. Can they be instrumented?

    Usually, yes. Older equipment can be read through PLC interfaces, retrofitted sensors or edge devices without touching the control system. We have built embedded and sensor firmware as well as the software above it, which matters when the answer is 'it depends on the machine'.

  • Does this require replacing our ERP or MES?

    No. We read from them and build the operational layer above, which is faster to deploy and does not put production at risk.

  • How do you handle plant floor networks?

    Carefully and with your controls engineers. Read-only wherever possible, segmented from the control network, and never a component that production depends on to run.

  • Can AI join shift logs to machine data?

    Yes. The log and the fault code describe the same event. We test against failures you have already had before the floor relies on it.

Do you know the rules that apply in the UAE, Saudi Arabia and the wider GCC?

For manufacturing that means ESMA and SASO conformity, In-Country Value programmes and ADNOC vendor standards. We read the rule before the call, so the first meeting is about your operation rather than about us catching up.

Whatever manufacturing needs here, we can make it.

What you already run stays where it is. Around it we build software, hardware and the process itself. Here that means a sensor and enclosure we build when the machine has no port.

See everything we build
  • Software
  • Hardware
  • Ways of working
  • Whole ventures

Honest about the numbers

The figure above is from BLS: Productivity and Costs by Industry, Manufacturing and Mining, for manufacturing.

We have not localised it, because a number nobody can check is worth less than a real one plus this sentence. The pattern travels. The size of it in your market is a question for the call.

Same industry, other markets