Best Predictive Maintenance Software (2026): Top 10 Compared

IBM Maximo Application Suite combines enterprise asset management with asset performance management. The predictive pieces are Maximo Health, which scores asset condition, Maximo Monitor, which watches sensor data for anomalies, and Maximo Predict, which estimates failure probability. IBM also promotes Maximo Condition Insight, an AI feature intended to surface emerging risks without data science work.

The suite is licensed through AppPoints, credits that each application and user type consume, so a buyer installs only the components it needs. It can run on premises, on AWS, Azure or Google Cloud as client-managed software, or as SaaS on AWS, and the licence includes Red Hat OpenShift, Db2 and the other supporting software.

Because the predictive applications share data with Maximo Manage, the suite suits organisations that already run or plan to run Maximo for work management.

AssetWatch sells remote condition monitoring as a managed service. Its team installs wireless vibration and temperature sensors on rotating equipment, connects them over its own cellular network and maintains the sensor network, so the plant needs no Wi-Fi or IT integration.

Readings feed an AI risk engine, and a dedicated certified Condition Monitoring Engineer reviews the output and sends prescriptive recommendations through the mobile app, web platform, email alerts and work order or CMMS integration. AssetWatch also offers oil analysis and shows lubrication data next to vibration and temperature trends.

The company states it serves hundreds of customers and that its sensors have gathered more than 5 million full-spectral vibration and temperature readings. Software licences are unlimited within a subscription. The $199 trial lets a plant test the service on up to 200 sensors before committing to an annual contract.

Shoreline AI, based in Campbell, California, describes its product as a plug-and-play physical AI platform for critical energy infrastructure. Its smart sensors run inference at the edge, send data directly to the cloud without gateways, and are self-installed by field technicians.

The platform draws on more than 30,000 pre-built asset physics models, which Shoreline says establish a baseline on the first day and remove the need for historical data. Human experts validate model output in the loop, and open APIs connect to CMMS and ERP systems. Coverage listed on the website runs from wellhead equipment and jet pumps to reciprocating compressors, engines, refinery blowers and power generation balance-of-plant equipment.

Shoreline also sells emission monitoring for methane and volatile organic compound leaks from slop tanks, compressors and relief valves. The subscription bundles sensors and software in a zero-capex arrangement.

Tractian, headquartered in Atlanta, sells wireless condition monitoring sensors, an AI diagnosis layer and maintenance software. This entry covers the condition monitoring product rather than the work order features.

The sensors measure vibration and temperature and connect over 4G/LTE with a range of up to 330 feet through obstacles. Tractian lists a battery life of 3 to 5 years, an operating range from -40°F to 250°F, an IP69K rating and Class 1 Division 1 certification under ATEX, IECEx and NFPA requirements. The platform flags developing failures, states how severe they are and suggests the next action, and adds root cause analysis and automated failure reports in the Bundle plan.

Integrations listed include SAP, Oracle NetSuite, IBM Maximo and Power BI, and Tractian also sells electrical and process monitoring.

Augury sells Machine Health, a subscription that combines wireless sensors, AI diagnostics and reliability experts. The company states it monitors more than 300,000 machines and has collected more than 1.1 billion hours of machine data.

Sensors capture vibration, temperature and magnetic data. Augury's coverage tiers are Critical for production-critical rotating assets, Hazardous for Class I and II, Division 1 and 2 environments, Ultra Low RPM for machines under 20 RPM such as kilns and large gearboxes, and Pulse for medium-criticality balance-of-plant equipment. Augury claims 75% fewer false alarms than threshold systems.

Diagnoses for critical machines are confirmed by certified analysts, and results reach teams through dashboards and CMMS or EAM integrations. Augury is now adding AI agents for operational roles on top of Machine Health data, and lists ISO 9001 and ISO 27001 certification.

Senseye Predictive Maintenance is sold by Siemens as part of its industrial digitalisation services. Siemens markets the product under its own name and lists it among its predictive services.

The product page frames the problem as predictive maintenance that never moves beyond isolated use cases because data is fragmented and specialists are scarce. Senseye combines industrial AI with maintenance know-how to show asset health, estimate failure risk and rank where to act first, without manual analysis by data scientists.

Siemens describes a maturity path from early condition monitoring through advanced prediction to enterprise-wide deployment. Published customer stories include BlueScope Steel in Australia, which uses daily case reports and KPIs, and the German dairy Sachsenmilch. Siemens also publishes podcasts and e-books on scaling predictive maintenance programmes.

Aspen Mtell is the predictive and prescriptive maintenance product of AspenTech, which has been a wholly owned subsidiary of Emerson since March 2025. The product sits in AspenTech's asset performance management portfolio.

Mtell starts with asset health monitoring built on industry-specific asset templates and then adds machine learning failure prediction. AspenTech states the models detect failure patterns up to 90 days ahead. An embedded failure modes and effects analysis library suggests the corrective action for each predicted failure, and the output is pushed into existing EAM and ERP workflows. Since the Emerson acquisition, Mtell connects with Emerson AMS vibration monitoring for closed-loop maintenance.

AspenTech cites the Argentine energy company YPF, where early detection of compressor and bearing failures is credited with saving 10 days of production.

GE Vernova sells Asset Performance Management software to power, utility and other energy operators. The suite aims to raise reliability, lower maintenance costs and reduce risk, and runs on a common platform where modules can be deployed one at a time or together.

GE Vernova presents APM as a response to retiring experts, inflation and the convergence of operational and information technology, and works with Amazon Web Services on hosting. The product page cites US Department of Energy figures for the gains APM can bring, including a 10% to 40% reduction in reactive maintenance, as industry benchmarks rather than its own results.

Published customer stories describe Xcel Energy moving from time-based to risk-based maintenance, and SOCAR Türkiye reducing reactive maintenance by 20%. Interactive online demos are available without a sales call.

Avathon is the company formerly known as SparkCognition. It adopted the new name in October 2024 and moved its headquarters to Pleasanton, California. Its Autonomy platform applies industrial AI to maintenance, operations, safety and supply chain work.

For predictive maintenance, Avathon describes semi-supervised models that catch known failure events through threshold deviations and also flag unfamiliar anomalies. Alerts are calibrated automatically from user feedback, and explainability tools show trend plots and histograms of what drives each anomaly. The models adjust as assets age and maintenance practices change.

Avathon's published examples include pitch bearing failures on wind turbines identified up to a year ahead and a combined-cycle gas turbine failure predicted a month in advance. Customers quoted on its site include National Grid, Ørsted and Airbus.

Uptake Technologies, founded in Chicago in 2014, now focuses on predictive maintenance for commercial vehicle fleets. In March 2026 Bosch announced a planned acquisition of Uptake to combine it with Bosch Connectivity Hub telematics and the FleetME ecosystem; the pages checked did not state whether the deal had closed.

Uptake streams voltage, pressure, temperature and other vehicle signals from a fleet's existing telematics provider. Its models compare each signal with healthy and degraded behaviour across similar vehicles and raise an insight with evidence, severity, the systems at risk and validation steps for technicians, aiming to prevent no-starts, derates and roadside failures.

Other modules include Risk Explorer for prioritising vehicles, Remote Diagnostics, Warranty claim identification, a Mixed Fleet Data Hub and filterable dashboards.