We stay until the numbers are real

Getting a plant live on AssetAI is less about software configuration and more about disciplined data entry — the platform is only as useful as the asset registry and masters behind it. Our customer success team runs that groundwork with you, in your plant, on your machines.

What Onboarding Actually Builds

Before any operator scans a QR code, four things have to exist in the system, and our checklist tracks each one as a live done-flag on your dashboard:

• Masters — failure mode/cause/remedy, safety measures, tools, service and criticality lists that every future work order depends on.
• Locations — plant, area, line, and functional location hierarchy so assets and work orders roll up correctly.
• Assets — code, category, type, OEM/make/model, location, owner, plus the commercial/warranty/AMC block and a criticality rating (High/Medium/Low).
• Work orders — the first breakdown/PM records entered against real assets, proving the flow end to end.

This sequence isn't a services formality — it's the actual order the What is a CMMS checklist enforces inside the product, because each layer depends on the one before it.

Why Masters Come First

Plants new to structured maintenance often want to skip straight to printing QR codes and logging breakdowns. We don't let that happen, for a concrete reason: closing a breakdown (BM) or corrective (CM) work order is hard-gated on failure cause and remedy being selected. If those masters aren't seeded correctly during onboarding, technicians hit a wall at closure — not later, but on day one.

Getting this master data right up front also matters beyond onboarding. Analytics like Pareto failure ranking and RRR (repeat-repair-rate) trending are only as consistent as the cause/remedy vocabulary your team started with — inconsistent naming at entry becomes inconsistent analytics for months afterward. This is the same discipline that underpins broader reliability practice such as Total Productive Maintenance, and it pays off later when you start reviewing OEE trends against real failure data.

What We Don't Do, and Why That's Deliberate

Customer success onboards your data and your team's confidence — it does not replace your maintenance function:

• We don't perform repairs or procure spares; AssetAI is workflow software, not a maintenance contractor.
• We don't run an automated historical data migration — asset and master entry is manual or CSV-driven work done during onboarding, not a bulk import engine.
• We don't train operators on machine-specific repair skills — the goal is comfort with the scan-and-report flow, not technical competence.
• We don't promise a specific breakdown-reduction or PM-compliance figure — outcomes depend on how consistently your team uses the system after go-live.

If your plant operates under ISO-aligned quality or safety frameworks, our ISO & standards page covers where AssetAI's data structure aligns with those requirements — and for sector-specific context on how Indian manufacturers are scaling maintenance practices, IBEF's industry data is a useful reference point. To see how this looks for your own plant, book a 30-minute demo — we'll run it on your assets, not a slide deck.

Getting a plant from zero to live is a sequence, not a single event — and knowing what happens in what order helps a maintenance head plan around it rather than be surprised by it.

How the Rollout Runs on Your Shop Floor

We don't open with a slide deck. The first working session is a demo on your own asset data: we scan an actual machine's QR code (or set one up live if it doesn't exist yet), enter an operator name and company PIN, and show the breakdown landing as a data record in front of you. That's deliberate — a plant considering AssetAI should see the scan-first mechanism working on its own equipment, not a generic screenshot, before committing.

From there, the same session moves into building out the pieces the What is a CMMS checklist tracks — location hierarchy, a sample of the asset registry, and the masters a technician will need to close a work order. We print and hand over QR codes for the machines covered so far, and your team tries the scan-report flow themselves, without a login or app install, while we're still in the room. What we're building toward is confidence in the mechanics: operators comfortable scanning and reporting, planners comfortable seeing the checklist fill in on the dashboard. Whether the platform fits your plant's ongoing needs — shift patterns, criticality mix, spare-parts discipline — is something you'll judge better once you've used it, which is why use cases and industries are worth a look before the call, not after.

What Stays With Your Team After Go-Live

Onboarding gets the registry, masters, and QR codes in place — it does not run your maintenance program for you. Once a plant is live, ongoing data entry, meter readings, and closing out breakdown and PM work orders are your team's responsibility, same as they would be with any CMMS. We don't perform repairs, source spare parts, or clean up years of historical maintenance records automatically — asset and master data entry during onboarding is manual or CSV-driven work, done deliberately so the fields are accurate rather than fast.

That boundary matters most around two things plants often expect but AssetAI doesn't provide out of the box:

• Permit-to-work or hazardous-job sign-off — the asset record carries a safety-measures list, but there's no approval-gate workflow layered on top; if your plant needs formal sign-off before hazardous work starts, that process has to sit outside AssetAI today.
• ERP/SCADA integration — onboarding covers the CMMS itself; connecting it to other plant systems is a separate conversation, worth raising on the demo call before assuming it's included.

Getting these boundaries clear early avoids the common mistake of treating go-live as "done" — the checklist finishing is the start of disciplined data entry, not the end of the project. Plants benchmarking against frameworks like TPM or tracking OEE will find the asset and work-order data from onboarding is exactly what those calculations depend on later — another reason the groundwork is worth doing properly the first time. If you want the full feature list before booking a session, /features and /pricing cover what's included at each stage, and our resources page has downloadable templates for master lists if you want to prepare data ahead of the call.