Reliable Assets. Predictable Maintenance. Report a fault in minutes. See downtime in ₹

AssetAI removes the friction that causes unreported faults — operators scan a QR code on the machine, enter their name and a company PIN, and the breakdown is logged without needing a login or app installation. Because the barrier is this low, breakdowns are captured at the moment they happen, when the operator is still at the machine. The system then enforces that every breakdown record must include a failure cause and remedy before it can be closed, which turns scattered reports into trustworthy data you can analyze later.

When a repair is completed, you need to know what it cost — and that cost is only complete when parts, contracted services, and labour hours all live on the same work order. AssetAI keeps these together so the true cost of each breakdown sits with the breakdown itself, not scattered across three different systems or spreadsheets. This gives you an accurate picture of which assets are expensive to repair, which feeds into your Repair / Review / Replace decisions later.

AssetAI runs preventive, usage-based (meter), calibration, statutory and lubrication schedules all from one daily job — each type of schedule raises its own work order according to its own trigger. A statutory inspection schedule and a preventive oil-change schedule on the same compressor will both appear in the work queue on their due dates, separated by schedule type. This means you can align all your compliance and maintenance rhythms in one place without juggling separate tools or spreadsheets, and nothing slips through because a schedule type wasn't covered.

Approvals are built into the work-order workflow, so you can route breakdowns or corrective actions up a chain (supervisor, maintenance manager, plant head) before they are actioned or closed. Each approval step is logged with a timestamp and user identity, which creates an audit trail. Combined with the fact that every change is written to an immutable activity log with field-level before/after values, this gives you the transparency you need across multiple plants and shifts without manually chasing sign-offs.

Yes — AssetAI is built as a PWA (Progressive Web App) that installs on your phone's home screen with four shortcuts for the most common tasks, and breakdown reports are captured and queued locally with no network required. When signal returns, the data submits itself automatically. This matters in Indian manufacturing plants where connectivity can be patchy on the shop floor; your operators can keep logging faults whether the internet is working or not, and the data synchronizes when connection is restored.

AssetAI calculates a Repair / Review / Replace score for each asset using plain arithmetic — historical repair costs, frequency, age and downtime — and prints the reasoning alongside the number so finance can see exactly which factors drove the recommendation. There is no hidden AI scoring or proprietary formula; you can defend the capex argument because the logic is visible. This approach is described in more detail under features, and the methodology is grounded in the same thinking as standards and frameworks used across Indian manufacturing.

AssetAI's task board shows open work orders in real-time with shift-specific assignments and handover notes. Incoming shift staff see what was attempted, what failed, and what needs continuation. Email/SMS alerts prevent tasks from falling into the gap between shifts.

Yes. Log manual readings—temperature, vibration, runtime hours—directly into AssetAI during rounds. The system flags trending patterns and suggests optimal intervals for greasing, bearing replacement, or inspection. Asset history builds over time to predict failures.

AssetAI works offline on tablets and phones. Work orders sync automatically when connection returns. This ensures no breakdown data is lost, even during outages—critical in plants with spotty connectivity or outdoor equipment areas.

Export repair cost trends, downtime hours, and spare parts spend from AssetAI. If a 12-year-old machine now costs 40% of annual budget to maintain, that ROI comparison is harder to ignore than gut feeling.