

Three screens from a live incident-triage run: the ops overview, the triage command, and the measured outcomes.
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Unplanned downtime is one of the most expensive problems in manufacturing. Industry studies put the average cost of unplanned downtime at around $260,000 per hour across sectors, and a single idle line at a large automotive or heavy-industry plant can cost on the order of hundreds of millions of dollars a year.
When a line stops, the technician on the floor checks the panel, calls the shift lead, digs through maintenance logs, texts the one person who fixed it last time, and waits for a callback. Traditional root cause analysis, when it happens at all, takes three to five days of manual correlation and lands on the wrong conclusion about 40 percent of the time. The answer to most production faults is already written down somewhere in your plant, in a work order from a few years ago, an OEM manual, or the head of a senior tech. AI incident triage exists to end that search.
Shakudo deploys a sovereign AI agent that reads all of it together: the PLC history, machine telemetry, maintenance records, past work orders, OEM documentation, and shift notes, and hands the technician the likely root cause with the fix the team has already used, in minutes. Incident triage drops from around seven hours to under ten minutes, and mean time to repair falls with it. The fix your team found in 2019 is found again in seconds. Past work orders and shift reports become searchable in plain language, and the tribal knowledge held by a handful of senior technicians is captured before they retire. With typical OEE around 45 percent and world class closer to 85, every recovered minute is production you ship.
Because the AI runs entirely on your own infrastructure, it can read the floor-level operational data that you cannot upload to a cloud AI vendor. That is what makes this triage possible in the first place. Most cloud APM and AIOps platforms need your OT data to leave the plant, and sensitive production and maintenance records often cannot. Sovereign AI on your own infrastructure closes that gap. The platform deploys in days, not months, and stays on your infrastructure, so the AI is yours, fully owned and controlled from model to memory.
Maintenance, operations, and reliability teams at plants, refineries, and production facilities where unplanned downtime costs real money and where OT data cannot leave the environment. Proven on production floors for a Premier Energy & Oil Producer and the World's Largest Wine Producer.
The AI reads the PLC history, machine telemetry, maintenance records, past work orders, OEM manuals, and shift notes together, and hands the technician the likely root cause with the fix the team has already used, in minutes. The seven-hour search becomes a ten-minute triage, and mean time to repair falls with it.
Cloud APM and AIOps platforms need your OT data to leave the plant. Shakudo's agent runs entirely on your own infrastructure, so it can read the floor-level operational data that you cannot upload to a cloud vendor, and the model stays fully owned and controlled from model to memory.
The AI captures it into a searchable form before they do. Past work orders, shift reports, and the fixes the team has already used become searchable in plain language, so the answer from 2019 is found again in seconds, not in a callback from a retired tech.
For production incident response, that means a line-down fault that used to cost your operation hours now resolves in minutes. Book a demo and see AI incident triage cut the seven-hour search down to minutes.
Shakudo deploys a sovereign AI agent that reads PLC history, machine telemetry, maintenance records, work orders, OEM manuals, and shift notes together, and gives floor technicians the likely root cause in minutes. The AI runs on your own infrastructure, so sensitive floor-level data never leaves your environment.