7 Top-Rated AI CMMS Software
Managing and maintaining complex asset portfolios takes a lot of work and coordination. Equipment breakdowns, unplanned downtime, and escalating maintenance costs can impact both productivity and profitability. To address these issues, maintenance managers can turn to AI-enabled computerized maintenance management systems (CMMS) that can predict equipment failures.
AI CMMS software uses predictive analytics, [1] machine learning, [2] natural language processing (NLP), [3] and generative AI models [4] to automate work order creation, optimize maintenance schedules based on real-time data, and provide actionable insights to enhance overall asset management.
This article lists seven top-rated AI CMMS software, sorted alphabetically, based on verified user reviews and our research team’s analysis. All products are dedicated CMMS solutions offering asset tracking, preventive maintenance, and work order management as the core features.
We selected products for this article based on their average ratings between August 2022 - August 2024, which may differ from their current overall average ratings.
1. Fiix
Fiix uses artificial intelligence (AI) to automate work orders, identify potential asset failures, and prioritize high-risk ones to prevent downtime. It compares work order completion times and productivity rates across shifts and locations to identify deviations in performance and recommends ways to improve resource allocation. The software examines past maintenance records and operational conditions to identify factors that could lead to delays, such as equipment wear or insufficient staffing. It also uses machine learning to calculate the optimal quantity and timing for purchasing parts based on historical usage patterns and upcoming maintenance schedules.
AI-enabled maintenance management features:*
Risk predictor: Forecast potential equipment failures and maintenance risks by analyzing historical data, such as failure logs and usage history, along with real-time inputs, such as equipment temperature, vibration, pressure, and noise, from IoT sensors. [5]
Inventory management: Analyze present inventory data, historical work orders, and upcoming maintenance schedules to determine the exact quantities and types of parts required.
Fiix Copilot: Use natural language queries to interact with AI assistant Fiix Copilot and get equipment-specific recommendations, such as optimal maintenance intervals, spare parts inventory optimization, and troubleshooting guidance.
Starting price: $45 per user, per month
Billing cycle: Annual
Customer support options: Call, email, knowledge base, and live chat
Who should consider Fiix’s AI capabilities?
Maintenance managers aiming to simplify troubleshooting processes can consider Fiix. Its Copilot feature delivers AI-driven recommendations that expedite diagnosing and resolving equipment issues. By leveraging natural language queries for guidance on optimal maintenance intervals, spare parts inventory, and troubleshooting, Fiix helps maintenance managers enhance operational efficiency, reduce downtime, and minimize the impact of equipment failures on productivity.
2. Fracttal
CMMS software Fracttal lets you upload asset data into the system, generate maintenance plans and work orders, and monitor maintenance activity using real-time analytics. Its failure mode and effects analysis features identify potential ways in which assets might fail, their causes, and their effects on the system. Its AI assistant, Tony, predicts equipment failure by analyzing asset characteristics and operating conditions. Tony also assists in scheduling maintenance personnel and troubleshooting issues by providing insights during the issue identification process. Fracttal's AI-powered scheduling feature optimizes maintenance schedules by considering asset criticality, technician availability, and maintenance priorities.
AI-enabled maintenance management features:*
Predictive maintenance: Monitor assets’ performance by tracking metrics such as temperature and vibration to identify issues and predict potential failures before they occur. You can proactively schedule maintenance to prevent asset downtime.
Inventory forecasting: Predict future inventory needs based on historical maintenance data, usage patterns, and upcoming work orders. You can use this analysis to maintain optimal stock levels for necessary parts and materials.
Maintenance analysis reports: Generate maintenance reports to gain actionable insights from current and historical work orders and asset performance. These reports help identify inefficiencies and improvement areas in your maintenance strategy.
Starting price: Available upon request from the vendor
Customer support options: Call, email, knowledge base, and live chat
Who should consider Fracttal’s AI capabilities?
Facility managers and maintenance supervisors looking to minimize stock-related interruptions during maintenance tasks can consider Fracttal. Its AI-driven inventory forecasting feature uses historical maintenance data and work order patterns to ensure necessary parts and materials are always available, optimizing maintenance scheduling and execution. This proactive approach reduces disruptions due to low stock and helps avoid emergency orders.
Pro tip
Evaluate your current maintenance challenges and identify specific areas where AI can provide solutions. Look into aspects such as frequent equipment failures, unplanned downtime, or scheduling and resource allocation inefficiencies. By understanding these pain points, you can select a CMMS that offers tailored AI features to address your unique needs—whether predictive maintenance, fault detection, or asset management.
3. Infraspeak
Infraspeak CMMS helps generate asset maintenance plans, including custom lift, fire safety, and HVAC system audits. The software simplifies work order management by automatically prioritizing tasks based on urgency, impact, and resource availability. Its AI functionality assigns tasks to the most suitable technicians, considering their skills, availability, and location. Like the other CMMS tools on our list, Infraspeak uses AI algorithms to analyze historical maintenance data and real-time sensor inputs and identify potential issues.
AI-enabled maintenance management features:*
Failure reporting: Use real-time data from sensors, such as humidity and vibrational levels and temperature readings, to identify anomalies and generate equipment failure reports. These reports include the nature of the issue, its cause, and recommended corrective action.
Inspection management: Analyze historical inspection data, equipment performance metrics, and environmental factors to determine the optimal frequency and scope of inspections. This AI feature generates inspection schedules, procedures, and reports.
Analytics and reporting: Gather data from maintenance logs and IoT sensors to create analysis reports. These reports help identify trends (e.g., recurring equipment failures, maintenance frequency) and correlations between different variables (e.g., impact of environmental conditions on equipment performance).
Starting price: Available upon request from the vendor
Customer support options: Call, email, knowledge base, and live chat
Who should consider Infraspeak’s AI capabilities?
Infraspeak is worth considering for maintenance teams that want to improve their decision-making processes. Its AI-enabled reporting feature analyzes maintenance data to reveal patterns and trends, such as recurring failures and environmental impact on equipment performance. This analysis enables informed decisions on scheduling preventive maintenance, allocating resources, and addressing root causes of issues. Moreover, real-time visibility into equipment health allows managers to prioritize critical tasks, ensure compliance with safety and regulatory standards, and improve maintenance strategies.
4. MaintainX
MaintainX is an AI-enabled CMMS tool that automatically generates maintenance checklists based on asset performance. These checklists cover regular inspections, safety checks, quality control, work orders, and compliance instructions. The software centralizes data on facility uptime, maintenance logs, and work orders, segregated by technician, equipment, and location, allowing you to monitor performance and get real-time visibility into operations. It also offers AI-driven insights into metrics such as asset performance, equipment failures, work order completion rates, and average time to repair, so you can optimize maintenance plans and resource allocations.
AI-enabled maintenance management features:*
SOP creation: Examine asset information to generate standard operating procedures (SOPs), including details about the task, materials required, and safety protocols. You can also customize the AI-generated SOPs by adding if-then conditional logic.
Anomaly detection: Analyze work orders to detect anomalies in asset data and alert technicians in real time. This feature helps identify early signs of technical faults and enables immediate corrective actions.
Smart voice memos: Create notes for work orders by recording voice clips and transcribing them using AI smart voice memos. This feature integrates transcribed work orders into maintenance plans for recording purposes.
Starting price: $16 per user, per month
Billing cycle: Annual
Customer support options: Call, knowledge base, and live chat
Who should consider MaintainX’s AI capabilities?
Maintenance managers who want to improve productivity by automating administrative tasks, such as documenting work orders, can consider MaintainX. Instead of manually typing out notes, managers can use smart voice memos to record their observations or instructions, speeding up the documentation process. Moreover, by converting voice recordings into text, the system helps ensure details are captured correctly and consistently, reducing the risk of errors or omissions that can occur with manual note-taking.
Pro tip
Focus on AI-driven asset management capabilities. By employing AI to assess asset health and performance trends, the system can create more accurate maintenance schedules and prioritize tasks based on actual needs rather than predefined intervals. This proactive approach helps minimize unexpected breakdowns, extend the asset lifespan, and reduce maintenance costs.
5. ManWinWin
ManWinWin CMMS enables you to create, assign, and track corrective and preventive maintenance work orders. Its AI capabilities prioritize tasks based on urgency and criticality. Its AI assistant, Winston, provides real-time alerts for potential issues, insights into equipment performance, and predictive forecasts for resource needs and potential failures. ManWinWin also helps track and manage the cost of maintenance activities, including labor, materials, and external services. Additionally, it offers a customizable dashboard to track KPIs such as average time between failures, repair times, total downtime, and work order completion rates.
AI-enabled maintenance management features:*
Alerts: Notify relevant team members about key maintenance issues, such as high equipment downtime, overdue or delayed work orders, and inventory requirements.
Insights: Get AI recommendations based on your maintenance activities. For example, the AI can suggest replacing equipment with high maintenance costs, adjusting ineffective preventive maintenance schedules, or resizing the maintenance team to match workload demands.
Forecasts: Analyze current work orders and historical maintenance data to provide AI-generated predictions regarding equipment breakdown time, time to repair, repair costs, and breakdown frequency.
Starting price: $42.18 per user, per month**
Billing cycle: Monthly
Customer support options: Call, email, knowledge base, and live chat
**Converted from EUR to USD on Aug. 1, 2024, using xe.com.
Who should consider ManWinWin’s AI capabilities?
ManWinWin is worth considering for maintenance teams looking to automate cost tracking for maintenance activities. Manual or Excel-based tracking of maintenance costs—whether related to labor, materials, or external services—can be prone to errors, time-consuming, and not provide real-time insights. ManWinWin’s cost tracking feature enables businesses to track all maintenance costs within a centralized system. Users can also generate reports to understand where costs are concentrated or where there may be inefficiencies to optimize spending and reduce overall maintenance costs.
6. TheWorxHub
TheWorxHub helps you create, track, and manage work orders from a consolidated dashboard. You can assign work orders to specific team members, set priority levels, and monitor each work order's progress. The platform also supports preventive maintenance by enabling you to schedule and track recurring tasks, with automated reminders to help prevent equipment failures and reduce downtime. Additionally, it enables you to track the location and condition of assets across warehouses to monitor stock levels and manage the reordering process.
AI-enabled maintenance management features:*
Inventory forecasting: Use maintenance data, asset usage patterns, and predictive analytics to estimate future inventory needs for maintenance parts and supplies. This feature analyzes the consumption rates of these parts to predict their reordering date.
Asset categorization: Use machine learning to classify and categorize assets based on attributes such as asset type, performance data, maintenance history, and operational context.
Compliance management: Review and analyze maintenance records and documentation to identify discrepancies. This proactive approach ensures compliance with environmental, health, and asset management regulations, such as the Occupational Safety and Health Administration (OSHA) standards.
Starting price: Available upon request from the vendor
Customer support options: Call, chat, and knowledge base
Who should consider TheWorxHub’s AI capabilities?
Facilities managers and maintenance supervisors who manage a large inventory of diverse assets can consider TheWorxHub. Its AI-powered asset categorization feature automatically classifies assets based on type, performance, and maintenance history, eliminating manual effort and creating a highly organized asset database. Moreover, understanding asset-specific attributes and performance patterns allows maintenance managers to develop tailored maintenance strategies, optimize resource allocation, and extend asset lifespan.
7. TRACTIAN
Similar to other CMMS solutions on our list, TRACTIAN uses AI algorithms to analyze data from IoT sensors installed on equipment and predict potential failures before they occur. The software suggests optimal maintenance actions, such as specific repairs, replacements, or adjustments, to prevent equipment failures. It assesses historical and real-time equipment data to predict when maintenance is needed. For example, if a machine shows signs of wear that typically precede a failure, the system can schedule maintenance before a breakdown occurs.
AI-enabled maintenance management features:*
Maintenance procedures: Create detailed procedures based on historical data, equipment performance metrics, and failure patterns. These procedures include details about recommended tasks, frequency, and specific instructions for each equipment.
Preventive checklist: Generate context-aware checklists of parts and supplies required for maintenance. These checklists specify the steps to be followed, the condition of equipment components to be inspected, and the necessary tools and replacement parts.
Inspection routes: Generate optimized inspection routes by analyzing equipment locations, conditions, and task urgency. Considering the facility layout and current equipment status, this feature plans the most efficient path.
Starting price: Available upon request from the vendor
Customer support options: Call, chat, and knowledge base
Who should consider TRACTIAN’s AI capabilities?
Maintenance managers overseeing complex equipment with intricate maintenance procedures can consider TRACTIAN to help technicians. By leveraging AI and machine learning, TRACTIAN generates detailed, step-by-step maintenance procedures and checklists, ensuring technicians have clear guidance. Additionally, the platform optimizes inspection routes based on equipment location, maximizing efficiency. These routes consider equipment proximity, task frequency, and technician availability, simplifying the inspection process and reducing travel time.
Pro tip
Opt for a CMMS that offers AI-driven failure mode analysis. This method uses artificial intelligence to analyze operating conditions, maintenance history, and failure patterns, helping pinpoint the underlying causes of equipment malfunctions. Based on this insight, maintenance teams can develop targeted strategies to address the root causes of recurring issues.
What are the benefits of using CMMS tools with AI capabilities?
AI CMMS tools simplify various operational and technical workflows. Below, we discuss some common benefits of the software based on its features.
Benefit | Description |
|---|---|
Predictive maintenance | By identifying patterns and anomalies that precede equipment failures, AI can predict when maintenance should be performed, preventing unexpected breakdowns. This reduces unplanned downtime and minimizes maintenance costs by enabling timely interventions rather than reactive repairs. |
Proactive risk management | AI models assess various risk factors by analyzing historical incident data, environmental conditions, and real-time inputs from sensors. These models can predict potential safety hazards and operational risks, enabling maintenance teams to take proactive measures to mitigate them before they escalate into serious issues. |
Optimized resource allocation | AI-powered tools evaluate work order priorities, technician availability, and skill sets to assign the right resource to the right task. This optimization reduces idle time, enhances productivity, and promptly addresses critical issues. Moreover, it enhances the planning and utilization of maintenance personnel, leading to cost savings and improved team performance. |
How much does AI CMMS software cost?
CMMS software offering AI capabilities can cost as low as $6 per month or up to $99+ per month, depending on various factors, including the available AI capabilities, number of users, reporting and analysis, chatbot, and integration. Most AI CMMS tools typically include the following pricing plans:
Free trials: Range from seven to 30 days and give users access to either all or limited AI features of the software. These no-cost trial plans are ideal for users who wish to try out a tool before purchasing it.
Free versions: Offer perpetual access to basic AI CMMS features, including automated work order generation and basic predictive maintenance. These free plans are ideal for small businesses on a budget.
Entry-level plans: Start at $6 per month and offer access to standard features. These are suitable for businesses with basic maintenance management needs, such as simple work order management, asset tracking, and basic reporting.
Mid-tier plans: Range from $11 to $59 per month and offer advanced AI-enabled CMMS features, such as advanced predictive maintenance, optimized resource allocation, and enhanced inventory management. These are suitable for businesses that have outgrown basic maintenance management tools but don’t require the full range of functionality offered by enterprise-level systems.
High-end plans: Costs more than $99 per month and offer a range of advanced AI capabilities, including unlimited features from entry-level and mid-tier plans, proactive risk management, energy consumption optimization, and advanced compliance reporting. These plans are suitable for larger enterprises with cross-functional workflows that need a high level of customization.
Hidden costs associated with AI CMMS software
Besides the software license, additional costs may include:
Implementation and training: Initial setup and training for your team can incur additional costs. This might involve hiring consultants or attending specialized training sessions provided by the vendor.
Data migration: Transitioning from an existing maintenance management tool to an AI-enabled one or exporting historical data might require help from the software support team, incurring extra costs.
Support and maintenance: While some plans include basic support, enhanced support services or dedicated account management often come at an extra cost. Regular maintenance and updates might also incur additional charges.
Frequently asked questions when selecting AI CMMS software
Here are some common questions to ask software vendors when evaluating AI computerized maintenance management software tools for your projects:
Can we customize the AI algorithm to fit our specific maintenance workflows?
Customizing AI algorithms is important because every organization has unique maintenance processes and operational requirements. For example, a manufacturing plant may need AI to focus on predictive maintenance for machinery, while a healthcare facility might prioritize equipment sterilization and compliance tracking. A one-size-fits-all AI solution may not address your needs, leading to inefficiencies. Tailoring AI algorithms to your workflows maximizes CMMS effectiveness, aligns with maintenance strategies, and enhances productivity.
What level of accuracy can we expect from AI maintenance predictions?
High accuracy means the AI can effectively predict equipment failures, optimize maintenance schedules, and prevent unexpected downtimes, leading to cost savings and improved operational efficiency. Conversely, low accuracy can lead to misguided decisions, increased costs, and a lack of trust in the technology. Understanding the expected accuracy helps set realistic expectations and gauge the potential return on investment.
How frequently are updates and improvements made to AI functionality?
Regular updates ensure the AI CMMS effectively addresses emerging maintenance challenges, adapts to new industry standards, and integrates with the latest technologies. Continuous improvements can enhance the system's performance, accuracy, and usability, providing you with the most advanced tools for maintenance management. The vendor should provide a roadmap or schedule for future AI developments, ensuring the system continuously evolves and remains up to date with emerging technologies.
Methodology
To be considered for this list, products had to:
Have at least 20 unique product reviews published on Software Advice within the past two years, with an average rating of 4.0 or higher (as of Aug. 1, 2024).
Meet our market definition for CMMS software: “CMMS software streamlines maintenance processes, management, and planning, helping organizations ensure consistent performance and increased efficiency. By automating and monitoring maintenance schedules, CMMS applications reduce costs and optimize the process of repair and replacement of vital equipment.”
Show evidence of offering AI capabilities as demonstrated by publicly available sources, such as the vendor’s website.
*Our research team identified these features from vendor websites (as of Aug. 1, 2024) based on their analysis of what users find valuable in or expect from AI-enabled CMMS software. This list is not exhaustive. For additional capabilities, refer to the vendor's website.
Research for this article was provided by Rakshat Chhokar.
For the section titled “How much does AI CMMS software cost?,” only products with publicly available pricing information and AI features, as of Aug. 1, 2024, were considered for pricing calculations.
Editorial independence: We select and rank products based on an objective methodology developed by our research team. While some vendors may pay us when they receive web traffic or leads, this has no influence on our methodology.
Definitions
Predictive analytics uses data, statistics, algorithms, and machine learning to predict future outcomes based on historical data. Predictive analytics is defined by four factors: a focus on prediction, a quick analysis measured in hours or days, a focus on the accuracy of the predictions, and a focus on how easy the analysis is to understand. In other words, predictive analytics has to quickly and easily predict realistic future outcomes based only on past data.
Machine learning (ML) is a computer science that uses data to learn like humans. It is a category of artificial intelligence (AI). ML uses data and algorithms for different technologies, including deep learning, neural networks, and natural language processing (NLP). ML can learn patterns and make decisions without human intervention by analyzing data.
Natural language processing (NLP) is an artificial intelligence technology that enables computers to understand human language. Computers do so by analyzing text and extracting meaning from it to perform tasks such as translating languages and understanding questions posed in natural language.
Generative AI refers to AI techniques that learn from artifacts or provided data to create new content similar to, but not identical to, the original. This includes generating text, images, videos, audio, structures, computer code, synthetic data, workflows, and models of physical objects.
Internet of Things (IoT) sensors are embedded in various equipment and machinery to monitor different parameters, such as temperature, vibration, pressure, and noise levels. They provide valuable insights into the performance and condition of assets, allowing organizations to detect anomalies and forecast potential failures.