Every minute of downtime is money, and the answer is in a manual nobody can find.
Hundreds of pages of manuals, old work orders and handwritten notes — on the shop floor, in a hurry.
8D reports, deviations and audit documents written and searched by hand.
OT networks without internet, and drawings and recipes that must never leave the site.
Downtime is the most expensive minute in industry — and the people who know the machines are retiring faster than they are replaced.
a year lost to unplanned downtime by the world’s 500 largest companies — 11% of their revenues.
per hour of downtime in a large automotive plant — more than $600 a second.
of unplanned downtime a month in an average large plant.
US manufacturing jobs could go unfilled by 2033 out of 3.8 million needed, as experienced workers retire.
average cost of a data breach in the industrial sector, up 18% in a year — the biggest jump of any industry.
Put your monthly volume into the calculator and see hours and dollars.
The path of one breakdown, from the alarm to the closed work order. Everything runs on site; drawings and recipes never leave the plant.
Manuals, drawings, SOPs, past work orders and 8D reports are loaded once and updated as they change.
KnowledgeOCR reads scanned manuals and handwritten notes; tables and part numbers are kept.
KnowledgeEverything is tagged by line, machine, component and part number and indexed on the plant server.
KnowledgeAn alarm from the MES or a question from a technician on a tablet starts a run with the machine ID.
FixSearch pulls the manual pages, similar past work orders and the fixes that worked on this machine.
FixA local model writes the troubleshooting steps from those sources, with the page and work-order number for each.
FixLock-out, high voltage or pressure work always shows the official procedure first and a warning to follow it.
FixThe technician speaks; Whisper transcribes on site and the model fills the work order fields.
RecordThe work order with parts and time is written to your CMMS through its API, for the supervisor to approve.
RecordAt shift end, open issues, alarms and work done are summarised for the next team.
RecordClosed work orders join the index, so the next breakdown of the same kind is solved faster.
RecordA local AI for a plant is a language model on a server inside the plant network. It knows the plant’s manuals, drawings, procedures and work-order history, answers technicians’ questions with the page it came from, writes work orders from dictation and drafts shift handovers and quality reports. It works offline, and drawings, recipes and know-how never leave the site.
Unplanned downtime costs the largest manufacturers 11% of their revenue, and much of a repair is spent looking for the right page or the person who fixed it last time. At the same time, experienced technicians are retiring. A local model keeps their knowledge where the next shift can find it.
Technicians get the fix in seconds instead of searching binders, work orders are complete without typing, and handovers are written for them. Safety, repairs and approvals stay with qualified people.
Typical minutes of technician and supervisor time per corrective work order. Your own numbers go into the calculator below.
Based on 43 min by hand and 8 min with local AI per item, from the table above.
The model searches, drafts and records. Safety, repairs and sign-offs stay with qualified people.
Lock-out and permit-to-work rules come first, always from the official procedure.
The model suggests steps; the technician decides and does the work.
Supervisors approve parts, time and closure in the CMMS.
Release, scrap and customer notifications are decided by quality.
Never written by the model to a machine.
Flip a switch to hand a step to the model or take it back.
Technicians get the answer from the manual and the plant’s own history in seconds, work orders write themselves, and the know-how of retiring experts stays with the plant.
We look at the documents and the work, agree what the model may and may not do, and size the hardware.
The model on a server in your network, on your real documents, with a small group of users.
Access rules, logging and integrations, then the whole team — with the old way kept as a fallback.
Model updates in maintenance windows, monitoring and a monthly report of use and time saved.
Yes. The model, the index and the interface run on a server in the plant network; it keeps working when the connection to the outside does not exist or goes down.
No. It reads alarms and data you choose to share and writes to the CMMS for approval. It never writes settings, recipes or commands to equipment.
They stay on the plant server. Nothing is sent to an outside AI service, and access follows your user groups.
It answers in their language, on a tablet or a phone, by voice if their hands are busy — and with the page in the manual so they can trust it. We start with one line and the people who run it.
One industrial-grade server with a 24–48 GB GPU per site is usually enough. It can sit in the server room or an edge rack on the floor.
Recorded walk-throughs and interviews are transcribed, turned into searchable notes per machine and linked to the manual pages they explain.
Describe your use case in two sentences — we reply within a day with a hardware and model recommendation.
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