Key Points
- Downtime is getting more expensive, not less. Siemens puts unplanned downtime at $1.4 trillion a year across the Fortune Global 500, equal to 11% of revenue, up from 8% in 2019 and 2020.
- "Unified asset health" is the fix for a specific problem: vibration data in one tool, electrical data in another, work orders in a third, and nobody holding the whole picture. Unified means one platform carries a fault from detection to a named diagnosis that lands in the system where work gets assigned.
- Seven platforms are worth evaluating, and they are not interchangeable. Only some sell their own sensors, only some get their findings into the system your technicians actually use, and only some name the fault instead of flagging a threshold. Those three differences decide what you get.
Full disclosure before you read further: this is Tractian's blog, Tractian sells a unified asset health platform, and Tractian is listed first. Every other platform here is described from its own documentation and from independent review data, including the limitations. You should still check our claims against theirs. That is what a real evaluation looks like.
What "unified asset health" actually means
The phrase gets used loosely, so it is worth pinning down.
Most plants already have asset health data. The problem is where it lives. A vibration route lives in an analyst's software. Thermal images live in a folder on somebody's laptop. Motor current data lives in the drive. Work orders live in a CMMS that knows none of it. Each system is defensible on its own, and together they guarantee that no one person ever sees the full condition of a machine.
A unified asset health platform collapses that. One place collects the condition data, diagnoses what is wrong, ranks it against everything else in the plant, and hands the technician a work order with the diagnosis attached.
That definition gives you six questions to ask any vendor:
- Does it sense, or does it only read? Some vendors manufacture sensors. Others are software that consumes data you already have. Both models work. They fail differently, and the second one gives you nothing if your plant is not instrumented.
- How many modalities? Vibration alone tells you about rotating equipment. Add electrical and you see the motor and the power feeding it. Add temperature, ultrasound, and oil analysis and you cover more failure modes.
- Does the diagnosis reach the people doing the work? A dashboard that alerts a person who then retypes the finding into a work order is two systems pretending to be one. The finding has to land where your technicians already work, whether that is the vendor’s own module or the CMMS you have run for a decade.
- Does it name the fault? "Vibration exceeded threshold" and "outer race bearing defect on the drive end, stage two" are different products sold with the same vocabulary.
- What does it cover? Many platforms handle rotating assets well and stop there. Plants also run electrical distribution, compressed air, steam, and process equipment.
- What does it need from you first? Some platforms assume a mature historian and a data team. That assumption is invisible on the pricing page and expensive in month three.
Hold every platform below against those six.
1. Tractian
What it is: A unified asset health platform combining first-party sensors, AI diagnostics, and integrates seamlessly with your existing CMMS. Tractian positions the category directly, leading with "Protect Your Operations. Cut Unplanned Downtime."
Sensing: Tractian manufactures its own hardware. The Smart Trac sensor captures triaxial vibration, ultrasound, magnetic field, and temperature from a single wireless point, with ultrasound running continuously rather than on a route. Electrical monitoring covers current and voltage on critical equipment, alongside utilities and process analytics. That range matters because a bearing starved of grease, a motor winding fault, and a power quality problem produce three different work orders, and most platforms see one of the three.
Diagnosis: AutoDiagnosis returns a large number of failure modes with criticality-based severity, rather than an anomaly score that leaves an analyst to work out what it means.
Execution: Tractian is CMMS-agnostic and integrates through API, SQL, or open integrations. The diagnosis lands in the maintenance system your technicians already open, with severity and procedure attached, so nobody retypes a finding from one tool into another.
Best fit: Manufacturers who want multi-modality sensing and named diagnostics across rotating and electrical assets, without changing the system where maintenance work already gets managed.
The tradeoff: Tractian is the asset health layer, not your system of record for maintenance work. If your CMMS is the actual problem, or you have no maintenance system at all, that is a separate purchase and a separate evaluation. Tractian makes the system you have smarter and does not stand in for one you do not have.
2. Augury
What it is: Condition monitoring hardware, AI diagnostics, and human reliability analysts sold as one subscription. Augury describes the diagnostics as prescriptive rather than only predictive, and its analysts hold Category III and IV vibration certifications.
Sensing: First-party. The Halo sensor covers triaxial vibration, two temperature channels, and triaxial magnetic flux, with product tiers for hazardous areas and for ultra low RPM assets below 20 RPM, which is genuinely hard to monitor well.
Execution: Not native. Augury integrates diagnostics into SAP PM, IBM Maximo, and Infor EAM rather than managing work orders itself.
Best fit: Plants with an established EAM they intend to keep, that want high-confidence diagnostics on rotating equipment with analyst backup.
The tradeoff: Scope is rotating assets. You will still need something else for electrical distribution and process equipment, and you will still need your CMMS. Worth noting that independent review volume is thin, with only three reviews on G2.
3. eMaint with Azima, from Fluke Reliability
What it is: The clearest CMMS-plus-first-party-hardware pairing on this list. Fluke Reliability acquired Azima DLI and integrated its diagnostics engine directly into eMaint.
Sensing: First-party. Fluke wireless triaxial vibration sensors feed the Azima engine, which Fluke says detects more than 1,200 fault conditions across 50 machinery component types, drawing on more than 30 years of diagnostic data.
Execution: Native, and the most explicitly documented auto-creation path here. When a reading crosses a defined threshold, eMaint generates a prioritized work order and routes it with asset history, linked manuals, and parts availability already attached.
Best fit: Teams that want vibration-led condition monitoring wired into maintenance execution, from a vendor with deep instrumentation credibility.
The tradeoff: Configuration burden is the consistent theme in independent reviews. eMaint holds 4.5 out of 5 across roughly 300 G2 reviews, where implementation complexity, limited form and field configurability, and restricted reporting output formats come up repeatedly. Budget real time for setup.
4. IBM Maximo Application Suite
What it is: The broadest scope in this roundup. Maximo brings enterprise asset management, asset performance management, and asset investment planning into one suite, with AI agents IBM names as Condition Insight, RCM Strategy Builder, and Alert Insights.
Sensing: None first-party. Maximo consumes operational, IoT, inspection, maintenance, and quality data from whatever you already have.
Execution: Native and central. Work management is the historic core of the product.
Best fit: Large, asset-intensive enterprises that need reliability strategy, capital planning, and compliance in the same system as maintenance execution, and that have the internal capability to run it.
The tradeoff: Implementation weight. Maximo holds 4.4 out of 5 across more than 600 G2 reviews, and the criticism is remarkably consistent: complex setup, steep learning curve, specialized knowledge required, dated interface, and high licensing cost. Reviewers describe correct setup taking months. That is a fair price for the capability, and it is not a small one.
5. Siemens Senseye Predictive Maintenance
What it is: Cloud predictive maintenance analytics, deliberately hardware-agnostic. Siemens describes it as working with existing data from legacy machines, historians, IoT platforms, or new sensors, with no new hardware required.
Sensing: None first-party by design. Senseye analyzes what you already collect.
Execution: Not native. Senseye forecasts failures, ranks risk, and estimates remaining useful life, which is one of the more specific analytical claims in this group.
Best fit: Multi-site manufacturers that are already instrumented, already have a historian, and need one analytical layer that scales asset intelligence across plants rather than another point solution per site.
The tradeoff: The hardware-agnostic model is also a dependency. ARC Advisory notes that predictive maintenance success rests on data quality and flags ongoing industry problems with data inaccessibility, inconsistent formats, and outdated documentation. If your plant is not instrumented, Senseye has nothing to read.
6. AVEVA Asset Performance Management
What it is: A process-industry APM suite built on real-time operational data, spanning predictive analytics, asset strategy optimization, and advanced analytics. AVEVA Predictive Analytics carries forward the product formerly known as PRiSM.
Sensing: None first-party. AVEVA consumes existing sensor and operational data, typically alongside the AVEVA PI System historian.
Execution: Not native to Predictive Analytics. AVEVA integrates with your existing CMMS, ERP, historians, and SCADA rather than replacing them.
Best fit: Chemicals, oil and gas, power, and utilities operations with a mature historian layer already in place and a strong preference for modeling flexibility, including the ability to add custom algorithms in Python.
The tradeoff: Two things. There is no native work order execution, so you need a CMMS to close the loop. And independent validation is close to nonexistent, so you will be relying on references and a proof of concept rather than peer review.
7. MaintainX
What it is: A CMMS and EAM platform built around mobile-first work execution, covering work orders, PM and PdM scheduling, parts inventory, digital checklists, safety inspections, and vendor management.
Sensing: None first-party. MaintainX ingests readings from existing sensors and from partners, notably AssetWatch, which supplies vibration monitoring backed by human analysts.
Execution: Native, and the partner loop is closed properly. When AssetWatch makes a maintenance recommendation, a work order is created automatically in MaintainX with the recommendation attached so the technician knows what to do. Work orders can also trigger on sensor readings, runtime, and failure codes. OT connectivity runs through Kepware, Ignition, HighByte, and MQTT rather than native protocol support.
Best fit: Teams whose first problem is maintenance execution and technician adoption, who want to add condition monitoring through partners as they mature.
The tradeoff: Reporting customization and per-user pricing are the recurring complaints in reviews, with some capability reserved for the Enterprise tier. And the condition monitoring depth belongs to the partner, not the platform, which is a different accountability model than a single-vendor stack.
How to choose
Three questions settle most of these evaluations.
Are you instrumented? If your plant already has sensors, a historian, and clean data, the software-only platforms are live options and they are strong. If you are starting from paper routes and a clipboard, a vendor that supplies hardware removes a project you would otherwise have to run yourself first.
Where does your work actually get managed? Wherever that is, the diagnosis has to land there. If you run a corporate EAM you are never leaving, the real question is how cleanly each platform writes into it and whether the finding arrives with enough detail to act on. If your maintenance system itself is the weak link, notice that some vendors here sell one and some do not, and treat that as a second evaluation rather than folding it into this one.
What breaks and stops you? Rotating equipment is the well-served part of this market. If your unplanned downtime traces to electrical distribution, compressed air, or process equipment, ask every vendor directly what they cover beyond motors and pumps, and get the answer in writing.
Ultrasound catches friction and lubrication problems earlier than vibration alone, which matters given how much bearing failure traces back to grease. Tractian is the exception among the seven here, capturing ultrasound and vibration from the same sensor. Among the other six, native ultrasound did not turn up, and where it appears it arrives through a service or a partner rather than the platform itself. Outside this list, some specialist condition monitoring vendors do offer ultrasonic and oil quality sensing, so if those modalities are decisive, widen your search beyond the platforms compared here.
Frequently asked questions
What is a unified asset health platform?
A unified asset health platform brings condition data, diagnostics, prioritization, and maintenance execution into one system. Instead of vibration data in one tool, electrical data in another, and work orders in a third, one platform carries a fault from detection through to a closed work order with the diagnosis attached.
How is unified asset health different from a CMMS?
A CMMS manages maintenance work: work orders, preventive maintenance schedules, parts, and history. It tells you what was done and what is due. Unified asset health adds the condition layer that tells you what is actually wrong right now, and delivers that finding into the CMMS so it becomes assigned work. The two are complements. Many CMMS products are adding condition monitoring through partners, which narrows the gap without fully closing it.
Do I have to replace my CMMS to get unified asset health?
No. Most platforms in this roundup, Tractian included, are built to integrate with the CMMS or EAM you already run rather than replace it. That matters because ripping out a maintenance system your technicians know is a change management project, not a software purchase, and it is the fastest way to stall an asset health program before it produces anything. Ask each vendor which specific systems they write into, what the integration actually creates on the receiving end, and who maintains it.
Do I need to buy sensors, or can I use the data I already have?
Both paths exist. Siemens Senseye, AVEVA, IBM Maximo, and MaintainX are software that reads data you already collect. Tractian, Augury, and Fluke Reliability supply their own sensors. If your plant is already instrumented with a working historian, the software-only route is faster and cheaper. If it is not, a hardware-inclusive vendor absorbs the instrumentation project instead of handing it to you.
Which platform is best for a single plant versus a multi-site enterprise?
Single sites usually do better with platforms that are fast to deploy and carry detection through to execution without a systems integrator. Multi-site enterprises with existing EAM standards tend toward analytics layers that scale across plants and feed the EAM they already run. The deciding factor is rarely features. It is whether you have the internal capacity to run a complex suite.
What does unplanned downtime actually cost manufacturers?
Siemens estimates the Fortune Global 500 lose $1.4 trillion a year to unplanned downtime, about 11% of revenue. In automotive, the same report puts the cost as high as $2.3 million per hour. Plant-level figures vary enormously, and teams commonly underestimate their own number because they count lost output and repairs while missing expedited parts, idle labor, overtime recovery, and customer penalties.
How long does it take to see results?
It depends almost entirely on your starting point. Vendors that supply sensors and a platform quote weeks to first findings. Enterprise suites like Maximo draw review comments describing setup taking months. Ask every vendor for a reference customer with a plant that looked like yours on day one, and ask that customer how long it really took.