Predictive maintenance watches equipment and tries to say when it will fail, which is a different job from the CMMS that records the repair.
This guide ranks on what the sensors and their installation really cost, whether the models work without a data scientist, and how much failure history a vendor needs before predicting anything.
Vendors can pay for visibility on this page. It never changes what an entry
says about a product, including the criticism, and we earn nothing when you click through to a
vendor. How that works.
In short
What predictive maintenance software does
Predictive maintenance software monitors equipment condition through sensors or existing signals, detects developing faults, and estimates how long a machine can keep running before it fails.
Five things, in this order. Feature counts are not among them: they are the least useful
comparison in software, because every vendor ticks every box.
01
Setup effort in predictive maintenance software
What the first ninety days of a predictive maintenance software rollout cost in hours, not in licence fees. A product that needs a partner engagement before it does anything is a different purchase from one a team configures in an afternoon.
02
What predictive maintenance software really costs
What the bill becomes once the modules a normal buyer of predictive maintenance software needs are added, and whether you can read that number without a sales conversation.
03
Getting your data out of predictive maintenance software
How your own data comes back out, in what format, and whether that export is included in the predictive maintenance software contract or billed as a project.
04
Independence from the vendor
Whether you can buy predictive maintenance software, run it and leave it on your own terms. This test decides most of the order on this page, and it is why the largest vendors in predictive maintenance software often sit below the smaller ones.
05
Who the product is built for
The size and shape of company each predictive maintenance software product was actually built for. Most regret in software comes from buying for a company you are not yet.
The fourth test decides most of the order on this page, and it is the reason the largest
predictive maintenance software vendors sit below the smaller ones. A product with a published price, an export
that works and no mandatory implementation partner is a product you can leave.
A platform suite that arrives with a quote, a partner and a two-year commitment may well be
the better software and is still the harder decision to reverse. We rank predictive maintenance software for the
buyer who has to live with that decision without a procurement department, which is a stated
bias rather than a hidden one.
We do not publish a score out of ten. A number like 8.4 is a judgement dressed as a
measurement, and nobody can check it.
What you can check is on this page: what each predictive maintenance tool costs, where the vendor is
established, whether the price is published, and what we think it is bad at. Our full method
is on the how we work page.
Quoted per organisation; modular enterprise licence
—
Power generators and heavy process operators with turbine fleets
A single factory monitoring a few dozen pumps
Country is where the vendor is headquartered or contracts from, which is a
different question from where your data is hosted. Where the two tell different stories, the
entry says so.
Reads motor current from the cabinet instead of mounting sensors
Ranked #1 of 12 in Best Predictive Maintenance Software in 2026.
Pricing on requestEurope
Measuring at the cabinet is the clever part: no shutdown, no mounting, no cabling on the machine, and assets in tanks or hazardous areas become monitorable for the first time. Water utilities and process plants get real value from that.
The physics also sets the boundary, because the electrical signature reflects the motor and its load rather than every component in the train. Reports arrive reviewed, which suits plants without an analyst.
What stands out
No sensors on machine
Electrical signature
EU vendor
Where it costs you
Sees only what the motor drives, not adjacent mechanics
Coverage stops where there is no motor control cabinet
Right for
Plants with pumps and motors that are hard or unsafe to reach
Wrong for
Monitoring gearboxes and equipment on separate drivetrains
NetherlandsSubscription per monitored asset, quoted
Energy monitoring first, machine condition as a second module
Ranked #2 of 12 in Best Predictive Maintenance Software in 2026.
Pricing on requestEurope
Sensorfact gets sensors into plants that would never have approved a predictive maintenance budget, by leading with energy waste that finance recognises. Once the hardware is in, the vibration module is an easy addition.
What you receive is monitoring plus a human interpreting it, not a model forecasting a failure date. For most mid-sized factories that is the useful step, but the wording in the sales deck deserves reading carefully.
What stands out
Energy and vibration
Self-install sensors
SME focus
Where it costs you
Condition monitoring rather than genuine failure prediction
Value depends on the vendor's analyst reviewing your data
Right for
Mid-sized European plants funding sensors through an energy business case
Sensors, monitoring and work orders from a single vendor
Ranked #3 of 12 in Best Predictive Maintenance Software in 2026.
Pricing on requestNorth America
Buying one contract instead of three is a real advantage, and the installation is genuinely quick because the sensors are magnetic and the gateway does the rest. The problem arrives if a CMMS already exists.
Technicians will not work from two lists, so either the new module wins and you migrate, or it loses and the alerts go unread. Decide which before the pilot, not after.
What stands out
Hardware included
Maintenance module
Fast install
Where it costs you
The bundled maintenance module competes with your existing CMMS
Proprietary hardware ties the subscription to one vendor
Right for
A plant with no CMMS wanting sensors and work orders from one supplier
Wrong for
Sites already committed to a maintenance management system
United StatesSubscription per asset, quoted; hardware included
Reliability engineers who also sell the monitoring platform
Ranked #4 of 12 in Best Predictive Maintenance Software in 2026.
Pricing on requestEurope
I-care sells expertise with software attached rather than the reverse, and for a plant where nobody can read a vibration spectrum that is the honest configuration.
Engineers install the sensors, review the data and tell you what to do, which removes the failure mode where alerts pile up unread. It is a service relationship with service pricing, and it does not get cheaper as your own team learns.
What stands out
Analyst service
Wireless sensors
Reliability consulting
Where it costs you
Highest ongoing cost of the options here
Little value if you intend to analyse in-house later
Right for
Plants with critical rotating assets and no reliability engineer on staff
Wrong for
Organisations building their own condition monitoring capability
Bolt-on vibration sensors for the balance of plant
Ranked #5 of 12 in Best Predictive Maintenance Software in 2026.
Pricing on requestEurope
OPTIME exists because the economics of traditional condition monitoring only ever worked for critical machines, leaving the rest to run to failure. Fixing a cheap sensor onto a fan and letting it join a mesh network changes that arithmetic.
What you get back is a bearing-focused verdict rather than an engineer's analysis, and Schaeffler's interest in selling bearings is visible in the framing. Correct for breadth, wrong for depth.
What stands out
Low cost per point
Self-install
Bearing expertise
Where it costs you
Shallow diagnostics compared with dedicated analysis platforms
Pulls the plant towards one component manufacturer
Right for
Covering hundreds of secondary machines that were never monitored
Wrong for
Deep analysis of a small number of critical assets
GermanySensor purchase plus annual subscription, quoted
Condition monitoring built on the sensors a plant already buys
Ranked #6 of 12 in Best Predictive Maintenance Software in 2026.
Self-hostablePublished pricingEurope
moneo is the option that behaves like industrial equipment rather than like a subscription: licences per module, installed on hardware you control, with data that stays on site.
For a maintenance engineering team that already specifies ifm sensors, that is coherent and independent. It is also work. Nobody interprets the data for you, the analytics are honest but basic, and mixing in other manufacturers' sensors is not the intended path.
What stands out
Sensor manufacturer
Modular licences
On-premise
Where it costs you
Analytics stop at thresholds and trends
Assumes standardisation on ifm sensors
Right for
Engineering teams that want to run monitoring on their own server
Wrong for
Plants wanting diagnoses delivered rather than built
GermanyPerpetual software licences per module, published list
Condition monitoring from the company that makes the bearings
Ranked #7 of 12 in Best Predictive Maintenance Software in 2026.
Pricing on requestEurope
SKF has been diagnosing bearing failures longer than most of this list has existed, and the hardware survives environments where consumer-grade sensors do not. Buying the analysts alongside it is a sensible option for plants without their own.
The frustration is commercial clarity: the portfolio has been renamed and restructured repeatedly, so working out which product you are being quoted, and what it excludes, takes persistence.
What stands out
Rotating equipment
Analyst option
Industrial hardware
Where it costs you
Product naming and portfolio boundaries change often
Everything is quoted through a sales engineer
Right for
Heavy industry with critical rotating equipment in harsh conditions
Wrong for
Buyers who want to compare a published price before a meeting
SwedenHardware purchase plus subscription and analyst services, quoted
Machine health diagnostics with a trained model behind them
Ranked #8 of 12 in Best Predictive Maintenance Software in 2026.
Pricing on requestNorth America
The distinguishing feature is the output. Instead of a spectrum for someone to interpret, you get a named fault, a severity and a recommended action, which is what allows a maintenance planner with no vibration training to act.
That accuracy comes from a large training set of rotating machines and is confined to them. The subscription is per machine per year, so covering a whole plant is a budget conversation, not a pilot.
What stands out
Named diagnoses
Rotating equipment
Managed service
Where it costs you
Limited to rotating equipment
Per-machine subscription becomes large across a plant
Right for
Plants with many motors, pumps and fans and no vibration specialist
Wrong for
Presses, robots and equipment outside the rotating class
United StatesSubscription per machine per year, quoted
Prediction layer over data you already collect, with no new sensors
Ranked #9 of 12 in Best Predictive Maintenance Software in 2026.
Pricing on requestEurope
Senseye is attractive because it skips the hardware project entirely: point it at the data you already collect and it estimates remaining useful life across thousands of assets.
Where the tags are rich and failures were recorded, that scales in a way sensor-based products cannot. Where the data is sparse, it produces very little and says so late. Since the Siemens acquisition, expect the commercial conversation to run through a partner.
What stands out
Sensor agnostic
Siemens owned
Scales to many assets
Where it costs you
Only as good as the signals your systems already record
Buying now runs through the Siemens partner channel
Right for
Large asset bases with existing controller and historian data
Wrong for
Plants with no historian and no maintenance history
United KingdomSubscription per asset, quoted through Siemens
Anomaly detection on historian data in process plants
Ranked #10 of 12 in Best Predictive Maintenance Software in 2026.
Pricing on requestEurope
The approach is sound for continuous processes: learn what normal looks like from years of historian tags, then flag the drift before an operator notices. Refineries and utilities have run it for years.
The unspoken requirement is a person. Models need building per asset, alarms need tuning, and the work never stops, so the product succeeds in organisations with a reliability engineering function and quietly dies in those without one.
What stands out
Process industry
Historian based
Model per asset
Where it costs you
A model per asset has to be built and then maintained
False alarms need continuous tuning by someone competent
Right for
Process plants with a historian and an engineer to own the models
Wrong for
Sites without existing process data or a reliability engineer
United KingdomSubscription credits under AVEVA Flex, quoted
Failure-pattern models for refineries and chemical plants
Ranked #11 of 12 in Best Predictive Maintenance Software in 2026.
Pricing on requestNorth America
Mtell is one of the few products here that genuinely predicts rather than detects, because its agents learn the signature that preceded past failures and watch for it again.
That design makes the data requirement explicit: without labelled failures there is nothing to learn from. Many buyers discover this after signing. If your maintenance history is a text field nobody filled in consistently, budget a year of data work first.
What stands out
Process industry
Failure agents
Enterprise
Where it costs you
Needs labelled failure history that most plants do not have
Enterprise licence and a long deployment
Right for
Refineries and chemical plants with recorded failure history
Wrong for
Plants whose maintenance records are free text and incomplete
United StatesQuoted per organisation; enterprise licence
Asset performance management for power and heavy process
Ranked #12 of 12 in Best Predictive Maintenance Software in 2026.
Pricing on requestNorth America
The SmartSignal model library is the asset here: years of remote monitoring across turbines and large rotating equipment, which is not something a newer vendor can assemble quickly. For a generator with a fleet, the reference cases are real.
Everything else is enterprise weight, from modular licensing to an implementation measured in years. Smaller plants comparing it against Augury or Samotics are comparing different categories of purchase.
What stands out
Power generation
SmartSignal models
Programme-sized
Where it costs you
Enterprise programme with modules, integrator and multi-year timeline
Overscaled for a single manufacturing site
Right for
Power generators and heavy process operators with turbine fleets
Wrong for
A single factory monitoring a few dozen pumps
United StatesQuoted per organisation; modular enterprise licence
Predictive maintenance software monitors equipment condition through sensors or existing signals, detects developing faults, and estimates how long a machine can keep running before it fails. The differences that matter are rarely in the feature list, so this is
the order we would work through them.
01
Decide whether you need a published price
1 of the 12 tools here publish what they cost; the other 11 quote per organisation, which means a sales conversation before you can compare anything. If you are buying without a procurement function, start with the ones that publish: ifm moneo.
02
Work out what the first ninety days cost in time
Licence cost is the number in the contract; setup effort is the number that surprises people. Ask every shortlisted vendor who does the configuration, how long it took the last customer of your size, and what happens if that person leaves halfway.
03
Check the exit before the entry
Ask for an export of your own data in a format you can open, and ask whether it is included or billed as a project. A vendor that hesitates here is telling you what renewal negotiations will feel like in three years.
04
Match the tool to the size you are, not the size you plan to be
Most regret in this category comes from buying for a headcount that never arrived. The entry-level products here are not worse; they are aimed at a different company.
05
Decide how much the jurisdiction matters
These 12 vendors are established in 6 countries across 2 regions (Europe 8, North America 4). Where a vendor is established decides which government can compel access to what it holds, which is a different question from where the servers are. For most buyers that is a factor, not a veto.
Most installations never reach prediction
The uncomfortable finding in this market is that a large share of deployments stop at condition monitoring and never predict anything. Prediction needs three things at once: sensor data at a useful sampling rate, a maintenance history that records why each machine stopped, and enough labelled failures of the same type for a model to learn from. Almost no plant has the third.
A pump that failed twice in five years, described in free text as bearing noise, is not a training set. Aspen Mtell is honest about this precondition and Senseye inherits whatever your historian holds. That is not an argument against buying. It is an argument for buying the monitoring, calling it monitoring, and starting to record failures properly today.
Count how many failures of one machine type you can describe with a date and a cause.
Ask the vendor what their model does in its first six months with no failure history.
Agree a failure coding standard for the CMMS before the sensors arrive.
This is not the CMMS, and the overlap is sold hard
Condition monitoring detects the fault. The CMMS raises the work order, holds the spare part, and records what the technician did. Two systems, and every vendor here would like to be both. Tractian bundles a maintenance module because a plant with no CMMS finds that convenient, and it is convenient, up to the point where you already have one.
The question to settle before signing is which system holds the work order, because if both do, technicians will use the one they already had and the alerts will pile up unread in the other. An integration that creates a work order from an alert, and closes the loop when it is completed, is worth more than any dashboard.
Name the single system of record for work orders, in writing, before the pilot.
Ask to see the CMMS integration working, not a slide describing it.
Check whether a completed repair feeds back into the model as a label.
What it costs to instrument a machine
The subscription is quoted per asset and looks manageable until you count the assets. Then there is the part nobody quotes: cable runs, an electrician, network coverage in a steel building, and a shutdown window to mount anything on a rotating shaft. This is why the products differ more in installation than in analytics.
Samotics reads the motor cabinet and touches no machine at all. Schaeffler OPTIME is fixed on and joins its own mesh. ifm moneo assumes you were buying sensors anyway. Senseye adds nothing physical and uses signals you already have. Price a pilot of ten machines end to end, including the electrician, and then multiply honestly.
Get an installed price per monitoring point, not a sensor price.
Walk the plant with the vendor and check network coverage at the worst location.
Ask what happens to the sensors and the data if you stop paying.
Who reads the alert at seven on a Monday morning
Every product here will eventually send an alert that turns out to be a loose sensor. What separates them is whether a human filters that before it reaches your technicians. I-care, SKF Enlight and Samotics put an analyst in the loop and charge for it, which is the right trade for a plant with no vibration specialist.
Augury does it with a model trained to name the fault rather than show a spectrum. AVEVA Predictive Analytics hands you the tuning job and expects you to have someone. Pick according to who you actually employ, because an alert stream nobody triages is turned off in month four, and the subscription runs to the end of the term.
Name the person who receives alerts and the one who acts when they are away.
Ask for the false alarm rate per hundred assets per month, in writing.
Agree an escalation path before go-live, not after the first missed alert.
What goes wrong most often when buying predictive maintenance software
Buying prediction when you have no failure history. Start recording causes in the CMMS this quarter; the models can come later.
Instrumenting the machines that are easy to reach instead of the ones whose failure stops the line.
Letting the condition monitoring tool issue work orders in parallel with the CMMS. Technicians follow one list, and it will not be the new one.
Judging the pilot on alerts generated. The only numbers that count are failures caught early and repairs that were avoided.
07
Frequently asked questions
10 answers
What is the best predictive maintenance in 2026?
Samotics leads our ranking of 12. SAM4 measures voltage and current at the motor control cabinet, so nothing is mounted on the machine and submerged or inaccessible assets can still be watched.
That also defines the limit: it sees the motor and what it drives electrically, not a gearbox on a separate shaft. Analysis comes back as a reviewed report rather than a raw dashboard.
How did you rank these predictive maintenance tools?
On what separates products after the demo: how much setup the first ninety days take, what the price becomes once the modules a normal buyer needs are added, how your data comes back out, whether you can buy and leave it without a partner engagement, and who the product is genuinely for.
That fourth test is why the large platform suites usually sit lower here than their market share would suggest. Not on feature counts, and not on a score we invented.
Which predictive maintenance tools publish their pricing?
1 of the 12, with the pricing model each one publishes:
ifm moneo: Perpetual software licences per module, published list.
The other 11 quote per organisation.
Is there a free predictive maintenance tool?
None of the tools here offer a usable free tier, which is itself a signal about who this category is sold to.
Which predictive maintenance tools can you host yourself?
ifm moneo. The other 11 are sold as a hosted service only, which means the question of where your data sits is answered by the vendor, not by you.
Where are these predictive maintenance vendors established?
In 6 countries across 2 regions: Europe 8, North America 4.
Samotics is established in the Netherlands.
Sensorfact is established in the Netherlands.
Tractian is established in the United States.
I-care is established in Belgium.
Schaeffler OPTIME is established in Germany.
ifm moneo is established in Germany.
SKF Enlight is established in Sweden.
Augury is established in the United States.
Senseye is established in the United Kingdom.
AVEVA Predictive Analytics is established in the United Kingdom.
Aspen Mtell is established in the United States.
GE Vernova APM is established in the United States.
Establishment decides whose courts and whose disclosure laws apply, which is a separate question from where the data is hosted.
What should you use instead of Samotics?
Sensorfact and Tractian are the next two on this page.
Sensorfact is for Mid-sized European plants funding sensors through an energy business case; Tractian is for a plant with no CMMS wanting sensors and work orders from one supplier. All 12 are ranked here with what each one is bad at.
Who should not buy Samotics?
Monitoring gearboxes and equipment on separate drivetrains. Sees only what the motor drives, not adjacent mechanics.
Do you get paid for these rankings?
Vendors can pay for visibility, which affects where and how prominently a product appears. It does not change a word of what the entry says about that product, including the criticism, and it cannot buy inclusion for something that does not belong in the category.
We take no commission when you click through to a vendor and we do not know whether you bought anything. The full arrangement is on our disclosure page.
How often is this predictive maintenance guide updated?
Whenever the facts move: a price change, an acquisition, a product that stops being maintained. The published and updated dates at the top of the page are real, and a review means someone went back to the vendor documentation rather than bumping a date.
These 12 products are the ones we judged worth ranking in predictive maintenance. If yours belongs here and is missing, tell us what it does and who it is for, and we will look at it. Inclusion is an editorial call and it is not for sale — but nobody gets considered for a list they were never put in front of.
People land on this page with a shortlist to make, not a browsing habit to feed. That is a narrower audience than a banner reaches and a far more decided one.
Written by us, about you
We describe the product in our own words, say who it suits and say who it does not. A vendor never writes the entry and never sees it before it goes up.
A correction costs nothing
If a fact about your product is wrong here, tell us and we fix it, whether or not there is any money between us. That offer is older than any commercial arrangement on this site.
Placement is separate, and disclosed
Where a product sits in the ranking can be paid for, and the notice above the list says so on every page. What the entry says about the product is not for sale at any price.
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