LogoUptime
Live monitoring active — 2,847 assets tracked now
97.3%
failure prediction accuracy

Every pump, conveyor, and compressor — watched in real time. Failures predicted weeks before the first vibration spike.

112
facilities monitored
< 6 wks
average deployment
$2.1M
avg annual savings/plant
SCROLL TO COMPARE
CMMS
77%fewer reactive work orders after 90 days

Your CMMS tells you what broke. Uptime tells you what's about to.

Legacy CMMS platforms are incident recorders. Uptime is a failure prevention system — the difference between a controlled shutdown and a $400K unplanned outage at 3 a.m.

IBM Maximo / SAP PMlegacy EAM
Mean Time to Resolution (MTTR)18.4 hrs
Unplanned Downtime %23%
Implementation Time14–24 months
Reactive vs Predictive Work Orders78% reactive
Annual Cost per Asset Monitored$340 / asset
Uptime AIpredictive platform
Mean Time to Resolution (MTTR)4.2 hrs
Unplanned Downtime %6.1%
Implementation Time4–6 weeks
Reactive vs Predictive Work Orders12% reactive
Annual Cost per Asset Monitored$94 / asset

Maximo migration not required. Uptime layers on top of your existing CMMS as a predictive intelligence layer — no data migration, no retraining, no IT project. Average go-live: 38 days from signed contract.

43%
reduction in MRO spend
averaged across 112 facilities over 18 months
Predictive Analytics
97.3%prediction accuracy validated across 2,847 assets

Not rule-based alerts. A neural model trained on 11 years of industrial failure signatures.

Threshold alerts fire when it's already too late. Uptime's failure signature library — built from 11M+ hours of rotating equipment data — detects degradation patterns invisible to vibration thresholds alone.

Rule-Based Threshold Alertinglegacy EAM
Failure Prediction Lead Time0–3 days
False Positive Rate34%
Asset Coverage (sensors required)Sensor-dependent
Time to First Prediction6–12 months training
Uptime AIpredictive platform
Failure Prediction Lead Time18–28 days
False Positive Rate2.7%
Asset Coverage (sensors required)Sensorless AI inference
Time to First Prediction14 days cold start
Failure detection timeline — centrifugal pump bearing
Day 0
Uptime detects micro-fatigue signature
Day 8
Work order auto-generated, parts ordered
Day 19
Scheduled replacement during planned shutdown
Day 22
Legacy system threshold alert fires — bearing seized
22 days
average failure prediction lead time
before the first vibration anomaly registers on a clipboard
Work Order Management
89%of work orders auto-generated from AI failure predictions

Work orders that arrive before the asset knows it needs one.

Uptime auto-generates prioritized work orders, pre-populates BOM requirements, and routes to the right technician — before a failure window opens. Your reliability team stops chasing problems and starts preventing them.

Manual WO / Basic CMMSlegacy EAM
Work Order Backlog (avg days outstanding)34 days
Auto-generated vs Manual Work Orders4% auto
Wrench Time (% of shift)28%
Parts Availability at Work Order Start52%
Uptime AIpredictive platform
Work Order Backlog (avg days outstanding)6 days
Auto-generated vs Manual Work Orders89% auto
Wrench Time (% of shift)61%
Parts Availability at Work Order Start94%
Run Your Benchmark

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No email required. No sales call triggered. Just the math, calculated against 112 real facilities running Uptime today.

$2.1M
average annual savings per plant
across facilities running 200–800 monitored assets
Inventory
43%average MRO spend reduction across 112 facilities

Order the right part 3 weeks early. Pay spot price never.

When Uptime predicts a bearing failure 22 days out, your procurement team has time to order at contract price, not emergency freight. Predictive demand signals eliminate the expedite tax that quietly erodes maintenance budgets.

Reactive MRO Procurementlegacy EAM
MRO Inventory Carrying Cost (% reduction)Baseline
Emergency Parts Expediting Events / year47 / year avg
Inventory Turns (MRO)0.8×
Stockout Events during Planned Maintenance1 in 3 WOs
Uptime AIpredictive platform
MRO Inventory Carrying Cost (% reduction)−43% avg
Emergency Parts Expediting Events / year3 / year avg
Inventory Turns (MRO)3.1×
Stockout Events during Planned Maintenance1 in 18 WOs
Integrations
< 6 wksaverage time from contract to live predictions

Connects to your stack in weeks. Not an 18-month IT project.

Uptime's integration layer is pre-built for every major EAM, CMMS, historian, and SCADA system in industrial use. No custom middleware. No data lake rebuild. Your existing infrastructure becomes the foundation.

SAP PM
EAMNative API
IBM Maximo
CMMSNative API
Infor EAM
EAMNative API
Emerson AMS
Condition MonitoringNative API
OSIsoft PI
HistorianNative API
Rockwell FactoryTalk
SCADANative API
Siemens SIMATIC
PLC / DCSConnector
GE Digital APM
APMNative API
Honeywell Uniformance
HistorianConnector
Fiix CMMS
CMMSNative API
UpKeep
CMMSNative API
Prometheus Group
Work ManagementConnector

Running something not on this list? Uptime's connector SDK supports any OPC-UA, MQTT, or REST-capable system. Our integration team has a 100% on-time go-live record across 112 deployments.