Unplanned downtime costs manufacturers $50 billion a year.
Most of it is preventable.
The data that predicts failures already exists in your maintenance logs, equipment sensors, and supplier records. The problem is that nobody has time to analyse it. These solutions turn your existing operational data into preventive intelligence.
$260,000/hr
Cost of downtime in automotive
Aberdeen Group
42%
Outages had detectable warnings
Deloitte Analytics Institute
30%
Maintenance cost reduction with predictive
McKinsey & Company
Preventive Maintenance Planning
The Problem
Your maintenance team manages 50 pieces of critical equipment. Each has different service intervals, manufacturer recommendations, and failure patterns. PM schedules live in spreadsheets, get overridden by production demands, and compliance hovers around 60%. Equipment runs until it breaks, and reactive repairs cost three times what preventive maintenance would have.
Solution Stack
PM Planner Agent
Analyses equipment records, manufacturer specs, and maintenance history
Equipment Maintenance Master Table
All critical equipment with service intervals, last PM date, condition, and priority
Maintenance History Log Table
Full history of every service event, parts replaced, and technician notes
Equipment Maintenance Library KB
Manufacturer manuals, service bulletins, and parts catalogues
Schedule Trigger: Sunday 8 PM
Weekly PM plan generated before the work week begins
Riley — Manufacturing Ops AI Employee
Autonomous coordinator that manages the full maintenance workflow
PM compliance ~60%
Scheduled maintenance frequently skipped due to production pressure
Reactive repairs
Equipment runs to failure; reactive repairs cost 3x preventive maintenance
Manual tracking
Spreadsheets, whiteboards, and tribal knowledge determine maintenance schedule
Parts shortages
Parts ordered after failure, not before — extending downtime by days
PM compliance 95%+
Every piece of equipment tracked with automated reminders and scheduling
Proactive parts ordering
Parts needed for upcoming PMs identified and ordered in advance
Data-driven priorities
Equipment ranked by criticality, failure risk, and production impact
Full maintenance history
Every service event logged automatically, building institutional knowledge
ROI Calculation
| Reactive-to-preventive shift | 50% of reactive work eliminated |
| Maintenance cost savings | $100,000/year |
| Prevented downtime events | 5 events/year |
| Downtime cost avoided | $25,000–$250,000 |
| Combined annual savings | $125,000–$350,000 |
Shifting 50% of reactive work to preventive saves $100K+/year. Five prevented downtime events = $25K\u2013$250K additional savings.
Quality Shift Reporting
The Problem
Your quality team produces a shift report at the end of each production shift. It takes 45–60 minutes of manual data collection, formatting, and analysis. By the time the report reaches management, the next shift is already two hours in. Critical quality issues that started in the first hour of a shift are not flagged until the shift is over.
Solution Stack
Quality Shift Report Agent
Collects production data, compares against targets, identifies defects and trends
Quality Shift Reports Table
12 columns: date, shift, line, units produced, defects, defect rate, top defect type, scrap cost, OEE, operator, notes, status
Scheduled Trigger: End of Each Shift
6 AM / 2 PM / 10 PM — report generated automatically at shift change
60 minutes manual compilation
Quality team manually gathers data from multiple systems at shift end
Delivered 2 hours post-shift
By the time the report reaches management, the next shift is well underway
Inconsistent formatting
Each quality lead produces reports differently — hard to compare across shifts
Delayed defect response
Critical quality issues discovered hours after they began
Report ready in 5 minutes
Automatically generated the moment shift ends — no manual data collection
Critical issues alerted immediately
Defect rate spikes trigger instant notifications before shift report is complete
Standardised format
Every shift, every line, every day — same structure, easy trend analysis
Trend detection built in
Agent identifies recurring defect patterns across shifts and lines
ROI Calculation
| Time saved per shift report | 55 minutes |
| Daily time saved (3 shifts) | 2 hours 45 minutes |
| Annual hours saved | 1,095 hours |
| Labour cost at $55/hr | $60,225/year |
| Faster defect detection value | Reduced scrap and rework |
3 hours/day saved across 3 shifts. 1,095 hours/year at $55/hr = $60,225 in direct labour savings. Plus faster defect detection reducing scrap.
Supplier & Procurement Intelligence
The Problem
Your procurement team manages 40 suppliers. Tracking performance, compliance certifications, delivery reliability, and financial health across all of them is a full-time job that nobody has time for. Supplier reviews happen quarterly at best. Between reviews, a critical supplier’s quality can deteriorate, certifications can lapse, or financial distress can go unnoticed — until your production line stops.
Solution Stack
Supplier Due Diligence Agent
Researches supplier performance, compliance, financial health, and risk signals
Supplier Registry Table
11 columns: supplier name, category, risk score, quality rating, lead time, on-time delivery %, cert expiry, last audit, spend YTD, contact, status
Condition Trigger: Risk > 70 OR Cert < 30 Days
At-risk suppliers and expiring certifications flagged automatically
Manual supplier tracking
Procurement team manages 40 suppliers across spreadsheets and email
Quarterly reviews at best
Performance reviews happen quarterly — problems emerge between reviews
Compliance blind spots
Certification expirations discovered during audits, not before
Reactive crisis management
Supply chain disruptions hit without warning; scramble for alternatives
Continuous risk monitoring
Every supplier scored and monitored in real-time against risk thresholds
Proactive cert management
Expiring certifications flagged 30 days out with renewal reminders
Performance trending
Quality ratings, delivery performance, and lead times tracked automatically
Early warning system
Financial health signals, news events, and risk indicators monitored continuously
ROI Calculation
| Supply chain disruption cost | $100,000–$500,000 per event |
| Compliance penalty risk | $50,000+ per violation |
| Procurement time savings | 15+ hours/week |
| One prevented disruption | Entire platform ROI for the year |
Identifying one at-risk supplier before failure = platform ROI for the year.
Three solutions. $185K–$660K in annual savings. Zero unplanned surprises.
Built from the same platform your office teams already use.
Which solution does your operations team need most?
Pick one. We’ll show you exactly how to deploy it — the agents, the tables, the employee configuration — in 30 minutes. Running in production this week.
Tell us your department and we’ll walk you through the exact configuration for your use case.