AI Predictive Maintenance Software

Predict Equipment Problems Before They Become Downtime.

Use IoT condition data, AI insights, maintenance history and automated workflows to detect abnormal asset behavior, prioritize risk, and trigger the right maintenance before failure disrupts operations.

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AI Predictive Maintenance • IoT Sensors • Condition Monitoring • Failure Risk • Automated Work Orders • Nested PM • Veda AI • Asset Analytics

Based on 200+ reviews on

  • INC 5000 2026
  • Globee Awards 2026 Gold Winner — Technology
  • capterra-shortlist-2026
  • software-advice-frontRunners-2026
  • Capterra Best Value-2025
  • G2 high performance

Maintenance technician using a mobile device
Asset HealthLive condition report • Compressor 04
Air Compressor 04Plant 1 • Utility Room

LIVE

82%Health Score

7.8 mm/sVibration trend
86°CTemperature
4,128 hRuntime

Live Vibration Trend
Alert threshold 8.0 mm/s
7.8 mm/s

AI Insight
Bearing degradation pattern detected. Inspect within 48 hours.

Predictive Work Order
AUTO GENERATED
WO-2094HIGH
AssetCompressor 04
IssueBearing Risk
DueWithin 48h
Generating maintenance plan87%

Assigning technician…
Parts + inspection steps prepared automatically.

AI + IoT + Mobile CMMS

Trusted By Global Brands Across The World

Veda AI for Predictive Maintenance

Ask which assets need attention before someone reports a breakdown.

Veda brings asset condition, work orders, maintenance history and sensor data into a conversational workflow. Ask what changed, which equipment is showing risk, and what work should be prioritized.

DetectSurface abnormal readings and recurring failure patterns.
ExplainConnect the risk signal with maintenance history and asset
context.
ActMove from insight to inspection, PM or corrective work.

Ask Veda

“Which assets have rising failure risk today?”
“Why is Compressor 04 vibration increasing?”
“Show similar bearing failures from the last 12 months.”
“Create a high-priority inspection for Compressor 04.”

See Predictive Maintenance With Your Asset Data

Walk through condition monitoring, AI insights, maintenance triggers and work orders using a real equipment scenario.

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Predictive Maintenance Outcomes

Move maintenance from fixed schedules to actual asset condition.

Use machine data and maintenance history to act when equipment needs attention—not simply because a date arrived on the calendar.

Reduce Unplanned DowntimeIdentify developing problems earlier and schedule intervention before failure.
Avoid Over-MaintenanceUse condition and usage data to improve when routine maintenance should occur.
Protect Critical AssetsPrioritize assets based on risk, condition and operational importance.
Improve Maintenance PlanningConnect predicted needs with work orders, technicians, parts and PM schedules.

Industry Recognition

Award winning CMMS software

Recognition from software review platforms for value, ease of use, functionality and customer support.

capterra-shortlist-2026
software-advice-frontRunners-2026
Capterra Best Value-2025
Getapp Best Function Feature-2025
Capterra Best ease of use-2025
Softwareadvice Best Customer Support-2025
G2 high performance

IoT Condition Monitoring

Watch equipment condition in real time.

Connect machine and sensor data with the asset record so maintenance teams can monitor changing conditions instead of waiting for inspections or failures to reveal the problem.

✓Vibration and FFT monitoring
✓Temperature and pressure readings
✓Runtime and meter-based data
✓Configurable trigger thresholds
✓Automatic condition history
✓Asset-specific alert rules

Live Condition Monitor
Vibration7.8 mm/sCritical
Temperature86°CWarning
Pressure7.1 barNormal
Runtime4,128hTracked

Predictive risk score: 72%

Automatic Maintenance Triggers

Turn a condition alert into maintenance action automatically.

When a reading crosses a threshold or a risk pattern appears, trigger the right workflow. Alert the team, create an inspection or work order, assign priority, and keep the condition event linked to the maintenance record.

✓Sensor threshold alerts
✓Condition-triggered work orders
✓Automatic technician notifications
✓Priority and escalation rules
✓Inspection or repair workflows
✓Complete event-to-resolution history

Condition Change

→

AI / Rule Trigger

→

Work Order

WO-2094 • Inspect Compressor BearingTriggered by vibration threshold • Priority High • Due within 48 hours
Parts RecommendedBearing 6205 • Seal Kit • Lubricant

AI Predictive Analytics

Use maintenance history to understand what the sensor reading means.

A number is only useful when it has context. Bring condition trends together with failures, repairs, downtime, parts and work history to help maintenance teams understand recurring problems and focus on likely causes.

✓Failure pattern analysis
✓Root-cause investigation support
✓Asset risk prioritization
✓Maintenance trend comparison
✓Downtime and reliability analysis
✓Recommended maintenance windows

Failure Pattern Analysis
Bearing Failure Risk

Vibration increase matches 3 previous bearing failures on similar
assets.

Want to See How DreamzCMMS Predicts and Responds to Asset Risk?

We can model a predictive workflow around your equipment, sensor data and maintenance process.

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Nested PM + Predictive Maintenance

Keep complex maintenance plans connected even when the trigger changes.

DreamzCMMS already supports nested preventive maintenance, allowing multiple maintenance activities and frequencies to remain under one parent plan. Add condition and predictive triggers so complex maintenance programs can respond to both schedule and actual equipment behavior.

✓Parent and nested PM schedules
✓Multiple activity frequencies
✓Labor tasks and technician guidance
✓Condition-triggered maintenance
✓Automatic alerts for each step
✓Complete PM and work order history

Compressor 04 • Master Maintenance Plan
Weekly
Visual inspection
Monthly
Filter and lubrication
Quarterly
Vibration analysis
Condition Trigger
Bearing inspection

Nested Activity Added AutomaticallyReason: vibration threshold exceeded • Linked to parent PM

Predictive Maintenance KPIs

Measure whether maintenance is becoming more proactive.

Use verified customer metrics where available. The dashboard should focus on operational reliability rather than generic AI claims.

Unplanned DowntimeTrack failure hours and emergency maintenance trends.
MTBFMeasure time between equipment failures and reliability improvement.
Failure RiskPrioritize assets with deteriorating condition or recurring issues.
Planned vs ReactiveSee whether more maintenance is being completed before failure.

Predictive Maintenance Integrations

Connect machine data with the systems your maintenance team already uses.

Bring IoT, FFT, ERP, asset, inventory and analytics data into a connected maintenance workflow.

Integrations

  • SAP
  • Sage Intacct
  • Stripe
  • Zebra
  • CIMCON
  • Oracle NetSuite
  • Intuit QuickBooks
  • Propelr
  • Microsoft Dynamics 365
  • Xero
  • Razorpay
  • Samsara
  • Odoo
  • TallyPrime
  • RevRex
  • PhonePe
  • Chainway
  • CardConnect
  • Codat
  • Siesa
  • Unleashed
  • Shopify
  • Monnit
  • Birdeye
  • SAP
  • Oracle NetSuite
  • Microsoft Dynamics 365
  • Odoo
  • Sage Intacct
  • Intuit QuickBooks
  • Xero
  • TallyPrime
  • RevRex
  • Stripe
  • Propelr
  • Razorpay
  • PhonePe
  • CardConnect
  • Codat
  • Zebra
  • Chainway
  • CIMCON
  • Samsara
  • Monnit
  • Siesa
  • Unleashed
  • Shopify
  • Birdeye

Already Have IoT or Condition Monitoring Hardware?

Show us what data your equipment produces. We can walk through how it can trigger maintenance inside DreamzCMMS.

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CMMS ratings and reviewsGet a quick view of CMMS ratings from trusted independent review platforms.
G2
Capterra
Software Advice
Up City

Where Predictive Maintenance Helps Most

Protect assets where a breakdown costs more than the repair.

MFG

Manufacturing

Monitor motors, pumps, compressors, conveyors and production equipment.

F&B

Food & Beverage

Protect refrigeration, processing, packaging and utility equipment.

UTIL

Utilities

Track distributed equipment condition, runtime and failure risk.

FAC

Facilities

Monitor HVAC, pumps, chillers and other critical building assets.

Predictive Maintenance FAQ

Common questions about AI predictive maintenance.

What is predictive maintenance software?

Predictive maintenance software uses asset condition, usage, sensor readings and maintenance history to identify developing problems and help teams schedule maintenance before failure occurs.

How is predictive maintenance different from preventive maintenance?

Preventive maintenance is usually scheduled by time, usage or meter intervals. Predictive maintenance uses actual condition and performance data to decide when equipment is showing signs that maintenance may be needed.

How does AI help predictive maintenance?

AI can help analyze patterns across condition data and maintenance history, highlight abnormal behavior, identify similar past failures and prioritize equipment that deserves attention.

What sensors can be used for predictive maintenance?

Common inputs include vibration, FFT data, temperature, pressure, runtime, current, acoustic data, meter readings and other equipment condition signals.

Can DreamzCMMS create maintenance work from sensor thresholds?

DreamzCMMS supports condition-based workflows where threshold events and maintenance rules can trigger alerts and follow-up maintenance actions.

What is Nested PM in DreamzCMMS?

Nested PM lets teams group multiple maintenance activities under a parent maintenance plan. Different nested activities can run at different frequencies while staying connected to the same asset and maintenance structure.

See AI Predictive Maintenance Working on Your Critical Assets.

Bring condition monitoring, IoT signals, failure risk, nested PM, automated work orders, Veda AI and maintenance history together in one DreamzCMMS workflow.

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