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.
Supply chain & industry
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.
Book a 20-minute call Free. No demo, no slides.
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
What is happening
The machine already said it. The person who needed to hear it was elsewhere.
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.
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.
Research
We wrote a full page on each of these, with the sources.
Each one carries its own figures and the citations behind them. Start with whichever sounds most like your week.
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.
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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.
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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.
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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.
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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
- PLC / SCADA
- OPC-UA
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.
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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.
Who this is for
The people who feel this first
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Plant Manager -
Operations Director -
Quality Head -
Maintenance Manager -
Supply Chain Director
Straight answers
The questions you would ask on the call
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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'.
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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.
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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.
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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.
Also in supply chain & industry
Supply chain & industry
Supply chain & logistics
Stockouts and excess inventory persist in organisations that bought every system designed to prevent them.
Supply chain & industryConstruction & infrastructure
And the average project still overruns by twenty-eight percent.
Supply chain & industryEnergy & utilities
Which is why the operation stays reactive when the data to be proactive already exists.
Next step
Start with your own numbers.
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We talk
20 minutes. Free.
You tell us what is not working. We ask how the work really gets done.
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We look at your data
A few weeks.
We read your systems, including the notes and letters no field holds. You get what is really in there, what it costs, and the accuracy we can hit.
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We build
A few months.
Only if step 2 says it is worth it. Fixed price, agreed before we start.