Maintenance teams spend most of the day chasing information. They don't have what they need in one place, so they search through SAP, emails, spreadsheets, conversations and long texts before they can even make a decision. Becoming proactive isn't another dashboard — it's the gradual return of control over the maintenance process.
Because everyone is busy, workorders don't always get closed correctly. PM plans slowly become outdated because the estimated hours no longer match reality. Priorities become less reliable. People stop trusting the ERP system and start keeping information outside it — which makes the data even worse.
At the same time, there is almost no real feedback loop. Execution happens, but very little of what is learned actually makes its way back into planning, scheduling or engineering. The same mistakes happen again and again because nobody has the time to structurally solve them.
The root cause
A handful of root causes both feed and are fed by the others. Teams chase information because the data can't be trusted. The data can't be trusted because the process isn't followed. The process isn't followed because everyone is too busy reacting. Each cause quietly recreates the next.
As long as the loop stays intact, individual improvements rarely last — the remaining root causes eventually recreate the same problems. That is why fixing one phase in isolation never holds.
Every improvement is deliberately balanced across the maintenance process, so progress in one area is supported by progress in the others. Instead of one improvement being offset by the remaining root causes, each improvement starts reinforcing the next — and the loop gradually reverses.
Over time it runs in the opposite direction. Instead of creating reactive maintenance, it starts creating proactive maintenance, while continuously reducing unnecessary work for the team.
Companies don't become proactive by implementing another dashboard or another planning tool. They become proactive by gradually restoring control over their maintenance process. That is why every GUSTY module is designed around the reality we see at almost every site.
We don't assume the data is clean. We don't assume the maintenance process is always followed. We don't assume everyone has time to keep the system properly maintained. We assume the opposite — because that is the reality. Poor data quality, inconsistent processes and incomplete ERP data are expected, not exceptions.
Four steps, in sequence. Each closes a specific operational gap, and each one makes the next possible. Every module delivers value on its own — together they form a complete closed-loop maintenance system.
You cannot plan proactively on data you don't trust. The first step is restoring the foundation. AI identifies workorders ready for closure and PM planning data that no longer reflects reality — the team confirms with one click, so nothing closes blind.
Execution is where planning succeeds or fails — and where almost nothing is normally learned. This step turns execution into feedback: the lessons learned are used to set up the Copilot and prevent the same execution issues from recurring.
With thousands of workorders in the backlog, priority and due date are no longer enough to decide what to schedule. The scheduling tool determines the true operational priority of every workorder and tells the scheduler when it can actually be scheduled — with the full context behind it.
Finally, the loop closes. The Copilot surfaces issues while there is still time to prevent them — or stops the same issue from happening again — so today's work automatically improves tomorrow's maintenance.
The goal
It's that maintenance teams regain control, stop firefighting, and have the confidence to plan proactively instead of constantly reacting. Better data and better numbers are a by-product of that control — not the other way around.
Each module delivers value on its own and can be implemented independently. In a typical Maintenance Operations rollout, the modules layer in over about ten weeks — from the KPI dashboard in week one to the Copilots by go-live — followed by a review and optimisation pass a few months later.
Three months after go-live: review, adjust & optimise.
Current pricing reflects our early adopter program. Customers who join during this phase keep their early adopter pricing, while pricing for new customers may change as the platform expands.
Current introductory pricing is available for early adopters.
The presentation walks through the problem, the root-cause loop, the four steps, a typical implementation timeline and the modules included.