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Industry · plants, quality, maintenance
AI in manufacturing
Production reporting automation and operational paperwork: the report builds itself from the data you already have.
🔊 With voice-over and subtitles
Where time is lost
- Protocols and operational paperwork are written by hand.
- Data is scattered across ERP, Excel and email.
- Management reports are pieced together by hand.
- Requests and quotes are slow.
We start with one process and measure. Production doesn’t stop: AI works alongside, on top of your systems, with a copy of the data.
What we automate
Shift → report
Shift data (ERP, Excel, notes) becomes a report for management (example).
Quality and maintenance protocols
The technician dictates, AI fills in the protocol template, a person approves (example).
Request → quote
AI gathers the data from the request and prepares a draft quote (example).
Scenario (example)
We don’t have a real case study in manufacturing yet. The scenarios on this page are examples, not client results.
Who takes part
- We start with the COO
- IT reviews data access
- The managing director approves the pilot
What directors ask us
Will production stop?
No. AI works alongside, with a copy of the data; lines and systems are not touched.
Our systems are old.
We work with old systems too: through file exports, reports or read-only access.
We have no IT capacity.
We handle the build and the support. We need the process owner and access agreed with your IT.
How do you measure the impact?
Before the pilot we measure how long the report takes today, and after the pilot we measure it again.
Related services: Process automation · Process analysis · Platform and third-party integrations
Next step
Show us one process that slows you down
In the demo you see a working solution on synthetic data instead of a slide deck. Then you decide whether to move on to analysis and a pilot.