The machines you own, running when they should be.
Downtime rarely arrives as downtime. It arrives as a workaround, a wait, a shrug. and it only becomes a number in a report written long after the shift that caused it. We name every stop, price it, and design it out.
Availability losses, ranked by cost, not by who complained loudest.
Three reasons downtime survives on a well-run floor.
The stop never gets recorded
An operator works around it, gets the line going, and moves on, which is exactly the right instinct and exactly why the cause never gets fixed. Nothing that isn't recorded can be ranked.
The fix waits behind a queue
A stretched maintenance team is buried in call-outs an operator could have handled: a reset, a latch, a guard door. The work that genuinely needs them waits.
The failure was signalled, quietly
Vibration creeping up. Bearing temperature up three degrees over a fortnight. Neither trips an alarm on its own. Together they are the signature of a failure you could still have planned for.
The agent that noticed both weak signals at once.
An agent has one job and never gets pulled onto something else. It reasons about what it sees rather than following a fixed chain of rules. When a decision carries weight, it stops and asks.
Four ways we take downtime out.
Each approach targets a specific cause of lost capacity by measuring real floor activity rather than relying on gut feel.
When OEE drops, the reason is usually buried in the line's own data. By the time it reaches a weekly report, the shift that caused it is long gone. Insights records every stop and state change as it happens, so you can ask why a cell dropped last night and get the answer from the machine itself.
OEE drops and finding out why is a manual scavenger hunt, often unnoticed until the weekly report.
Losses pinned to a root cause in minutes. Ask why Cell 3 dropped last night and get an answer from the line's own data.
Assistant, grounded in years of maintenance records, lets an operator describe what they are seeing and get the steps that worked last time. The line is back running in minutes, and maintenance is freed for the jobs that genuinely need them.
A stretched maintenance team is buried in call-outs an operator could have handled, so urgent work waits behind avoidable tickets.
Operators ask what they're seeing and get safe, guided steps drawn from how similar issues were resolved before.
Maintenance that is reactive or calendar-based either acts too late or far too often. Agent models your own equipment history to learn the patterns that precede failure, then watches for them around the clock. correlating weak signals no single alarm would catch.
Maintenance is reactive or calendar-based; the patterns that predict failure sit in records no one models.
Patterns specific to your equipment surface early, so an alert arrives with time to act on it at a planned stop.
Agent assembles a structured handover from the systems themselves, carrying open issues across with full context so nothing is lost between shifts and the next crew starts already knowing where to look.
Handover depends on a tired person remembering and the next shift reading it, so late issues fall through the gap.
A structured handover generated automatically, with late-breaking issues carried over in full context.
Improve quality →
Stop spending running time making parts you'll only throw away.
How it worksThe three layers →
What measures the stops, what explains them, and what watches for them.
StartDiscuss a production problem →
Pick your worst-performing cell. We'll show you what's really stopping it.