Report:

Magic Quadrant for Process Mining Platforms

Top Vendor Products for Process Mining Platforms in 2025

• Apromore
• ARIS (Software GmbH)
• Celonis
• IBM
• MEHRWERK
• Pegasystems
• SAP Signavio
• UiPath

Process Mining Platforms Vendor Product Comparisons 2025

• Apromore - Leader
  

  Pros:

  • Product innovation: Apromore has enhanced its core process discovery and analysis capabilities with improved visualizations. It continues to invest in GenAI capabilities by offering Apromore Copilot for redesign and simulation, process discovery, and optimization.
  • Product strategy: Apromore provides premade product assets, such as dashboards, KPIs, filters, integration pipelines, and connectors for specific processes and systems. This enables end users to start quickly with process mining.
  • Customer experience: Apromore scores highly for customer satisfaction, and Gartner Peer Insights reflects this. Apromore's no-code environment enables process mining practitioners to speed time to insights, simulate suggested changes, and implement continuous monitoring, alerts and dashboards.

  Cons:

  • Dashboarding: Apromore's dashboarding capabilities still have room for improvement. Some end users have reported on both Gartner Peer Insights and inquiry calls that the interface could be more user-friendly and customization options could be improved.
  • Geographic strategy: Apromore remains confined to certain geographic markets. It still depends heavily on partners for deployment and support assistance. This creates a barrier for prospective clients in EMEA and Latin America.
  • Operations: Apromore does not support on-premises deployment, which may affect end users who require on-premises solutions for compliance, data sovereignty or specific security policies. However, customers can deploy Apromore on their own private cloud as an alternative.


• ARIS (Software GmbH) - Leader
  

  Pros:

  • Product strategy: ARIS Process Mining supports task mining through ARIS Robotic Process Discovery, utilizing two OEM products. For buyers, this offers flexibility: the ProcessMaker-based task mining solution is suited for SaaS customers, capturing event data from users' operating systems, while the Nintex-based task mining solution caters to on-premises customers, using screen capture to collect user tasks. This dual approach allows buyers to choose a solution that best fits their infrastructure and operational needs.
  • Sales execution: ARIS has one of the largest customer bases in the traditional enterprise business process analysis (EBPA) space, which it leverages to promote its process mining offering. Its dominant position in governance, risk and compliance (GRC) use cases helps extend process mining to a large audience.
  • Marketing execution: ARIS has expanded its marketing scope to promote its benefits and synergies with the ARIS Process Intelligence Suite. It also targets key messaging to support a variety of customer maturities from those new to process mining to more advanced enterprises.

  Cons:

  • Sales execution: After the demerger of Software AG into two separate businesses in January 2025, ARIS now operates independently, with an independent employee base. Prospective customers should carefully evaluate the new structure — and its potential impact on product support, innovation, and strategic direction — to make informed decisions.
  • Customer experience: Customers report a high learning curve and insufficient training for ARIS Process Intelligence, especially for customers new to process mining. The offering requires extensive support and time to obtain value because of the extensive features offered.
  • Sales strategy: The vendor positions process mining in existing ARIS accounts under the umbrella of process intelligence and cross-sells with modeling and GRC. This can also create a barrier for clients looking for a platform of choice for general-purpose process mining.


• Celonis - Leader
  

  Pros:

  • Sales execution/partner network: Celonis operates as a stand-alone, system-agnostic platform in a highly competitive market and has one of the largest partner networks across geographies. With the largest customer base, its market share is estimated to be approximately 50%, which complements its future innovations, such as Process Intelligence networks that enable real-time data sharing across organizations using a hub-and-spoke model.
  • Product strategy: Celonis continues to enhance process discovery by offering multiple experiences. These include explorations, starter kit dashboards, the LLM-powered Process Copilot, more than 400 Celonis apps and over 350 partner apps to identify targeted improvement opportunities.
  • Product innovation: Celonis has innovated by offering a fully OCPM-compliant platform and Celocore for handling process mining at scale. Its planned innovations focus on AI-driven process intelligence, integration of the orchestration engine, and development of process intelligence networks for real-time data sharing. Partnerships with over 300 universities and research institutes in over 40 countries contribute to projects, research and patents, thus fueling a pipeline of innovation.

  Cons:

  • Market responsiveness: Gartner clients mention the complexity of the new OCPM platform for simpler use cases. Though the vendor has worked to reduce implementation times, it requires more advanced maturity for creating the right analysis and reporting, even for traditional use cases, because of the abundance of interconnected objects and processes.
  • Sales execution/pricing: End users still describe problems adapting to Celonis' pricing, even though the vendor has worked to simplify its pricing structure. In particular, users express challenges with changing pricing metrics, process-based costs, unclear scaling mechanisms and a high number of add-on SKUs.
  • Customer experience: Though the vendor has worked to expedite time-to-value realization, clients refer to a steep learning curve required to make the most of the platform's functionality. On Gartner Peer Insights, customers mention complaints on Celonis' service desk support.


• IBM - Leader
  

  Pros:

  • Product strategy: IBM Process Mining goes beyond diagnostic analytics, offering actionable, ROI-driven recommendations through prescriptive AI. The inclusion of Prescriptive Process Mining and IBM Process Mining Assistant enables end users to uncover advanced insights and next best actions.
  • Vertical/industry strategy: IBM differentiates itself from other process mining vendors by using a large number of subject matter experts and global integrators to deploy industry and vertical accelerators, facilitating industry-specific implementations. This approach enables IBM to offer tailored vertical solutions.
  • Product innovation: IBM is fully OCPM-compliant. Its OCPM-compliant data model enables users to manage an organization's entity-relationship diagram from a data perspective. Additionally, IBM's updated simulation experience allows users to set goals and utilize data-driven simulation capabilities.

  Cons:

  • Customer experience: Clients, as well as reviewers on Gartner Peer Insights, report that the initial learning curve is steep, the platform is complex for nontechnical users, user training could be better, and platform onboarding is complex. Reviewers mention the challenges for new users and the need for an improved user experience.
  • Market understanding: IBM focuses mainly on intelligent automation use cases, although it still supports process mining as a stand-alone offering. This creates a barrier for clients looking for a platform of choice for general-purpose process mining.
  • Pricing strategy: IBM's pricing is complicated, compared with that of other vendors. In particular, clients implementing the product on-premises have mentioned the complexity of pricing metrics.


• MEHRWERK - Leader
  

  Pros:

  • Market vision: MEHRWERK offers digital twins of business processes that can help end users simulate and optimize workflows in real time. Using predictive analytics with the insights of OCPM, end users can identify inefficiencies, predict outcomes and improve process resilience. For buyers, incorporating digital twins and OCPM can shift process management from reactive analysis to proactive optimization.
  • Product strategy: MEHRWERK's key differentiator is that it provides process mining with an open-platform strategy, which integrates directly into existing infrastructures. End users often mention the benefits of its modular and platform-agnostic design.
  • Process orchestration and execution: mpmX execution is a solution that can execute business processes by orchestrating manual tasks, application automation and workflows. It benefits the end users by combining the orchestration insights provided by OCPM and execution.

  Cons:

  • Geographic strategy: MEHRWERK has a limited presence outside Germany, relying on partners. Prospective customers considering MEHRWERK should confirm its support in all the regions in which they operate.
  • Operations and innovation: MEHRWERK is undergoing a carve-out process. Due to the complexity of the process, MEHRWERK was not allowed to share detailed innovation plans and financial figures for this year's evaluation.
  • Customer experience: Gartner clients sometimes mention the challenges with product documentation and user training. Additionally, clients mention that the limitations of the Qlik (data visualization) platform have impacted collaboration and visualization performance in their process mining projects.


• Pegasystems - Leader
  

  Pros:

  • Marketing execution: Compared to vendors from adjacent markets such as BPA and RPA, Pega offers a more comprehensive vision for process mining. It enables clients to both discover and monitor processes, benefiting end users who require process mining not only for monitoring but also uncovering new processes.
  • Geographic strategy/partner network: Pega has a strong partner network, with over 250 partners categorized as Global Elite, Specialized, Authorized and Registered. This benefits end users by enhancing the availability and delivery of Pega solutions, including process mining training and support.
  • Market responsiveness: Pega's R&D strategy focuses on quick delivery, updating the platform every nine weeks. Product development teams, organized into tribes, focus on continuous improvement. The Process and Task Mining Tribe achieved over 10 deployments last year, introducing new connectors, API extensions, security enhancements, integration advancements, and the GenAI-powered Process Mining Assistant, providing clients with the latest features and improvements.

  Cons:

  • Sales execution: Pegasystems focuses more on automation use cases, using process mining as an enabler for its broader process automation platform. This approach may create a barrier for clients seeking a platform specifically for general-purpose process mining.
  • Operations: Pega does not support on-premises deployment, which may affect end users who require on-premises solutions for compliance, data sovereignty or specific security policies.
  • Product strategy: Pegasystems' current lack of support for OCPM limits the tool more than traditional process mining. This is because OCPM broadens the way data is collected and processed, and enables users to see events and objects in all their states along different processes.


• SAP Signavio - Leader
  

  Pros:

  • Market vision: SAP Signavio emphasizes process mining as key to enterprise observability, aiding business transformation in operational excellence, customer experience and risk management, and enterprise architecture. SAP Signavio envisions the adoption of agentic models, real-time data and automated decision making, enhancing the interconnection of systems, and ultimately establishing a digital twin of an organization (DTO).
  • SAP client ecosystem: SAP Signavio offers bundled packages with specific value accelerators and promotional deals that include Signavio and other SAP solutions. This makes it easier for existing SAP clients to use process mining within their operations.
  • Vertical/industry strategy: SAP's process domain expertise and prebuilt value accelerators support enterprises across various industries, offering end users targeted solutions. With the offering's industry-specific benchmarks expanding from 26 in 2023 to 184 in 2025, end users can access more in-depth and tailored industry standards within the platform.

  Cons:

  • Sales execution: SAP Signavio focuses primarily on SAP-related use cases. Clients considering using process mining outside the SAP ecosystem should check the experience level, pricing and support that SAP Signavio and its implementation partners deliver.
  • Product marketing: Confusion remains about the difference between SAP Signavio Process Intelligence (a general process mining platform solution) and SAP Signavio Process Insights (a process analytics platform for SAP, created on the SAP Business Technology Platform). This is especially true for clients new to process mining. Clients would benefit from assessing a single process mining platform.
  • Product strategy: SAP Signavio does not support OCPM. Supporting OCPM allows businesses to gain deeper insights into their process orchestration, manage process complexity effectively, and unlock new efficiencies through deeper insights into all states and stages of objects and events. Clients who seek to go beyond mining individual processes and require a more-holistic process intelligence across their enterprise should check that SAP can meet these requirements.


• UiPath - Leader
  

  Pros:

  • Sales execution: UiPath has a significant global presence and targets various client demographics, verticals and maturity levels. Its product can be sold as stand-alone or positioned to support existing UiPath clients as an additional platform component.
  • Sales strategy: UiPath has accelerated release timelines, from testing to general availability. Its community of users contributes to product feedback. UiPath's other mechanisms for capturing customer requirements include customer surveys, advisory boards and CIO councils, all of which contribute to high levels of customer satisfaction.
  • Product strategy: UiPath Autopilot helps democratize process insights for end users. It enables users to query and filter data, and perform analysis. UiPath AI Trust Layer is a new native responsible AIOps capability that ensures the privacy of organizational data when using UiPath's GenAI solutions and third-party LLMs.

  Cons:

  • Product innovation: UiPath does not yet offer OCPM. Clients who want to go beyond mining individual processes and require a more holistic process intelligence across their enterprise should check that UiPath can meet these requirements.
  • Marketing execution: As evidenced from our end-user interactions, UiPath focuses more on intelligent automation use cases. Although it offers process mining as a stand-alone offering, this might create a barrier for clients looking for a platform of choice for general-purpose process mining.
  • Sales execution/pricing: End users have reported that UiPath's pricing model is complex. The vendor has worked to simplify the pricing structure. However, clients from small and midsize enterprises have commented, in their interactions with Gartner, that UiPath's pricing can be high, especially for those new to process mining that struggle to justify the investment.


• ABBYY - Challenger
  

  Pros:

  • Product strategy: ABBYY's Phoenix 1.0 is a purpose-built multimodal model that combines image and text analysis. It offers more accuracy than general-purpose language models. It enhances task-mining capabilities (by providing additional context, it supports the broader scope of process mining), and supports discovery with additional context in process mining.
  • Scalability: ABBYY has enhanced its big data management capability. The platform can now handle billions of data points. This enables organizations to monitor event-driven processes that span multiple years in a single repository. This capability is a differentiator, as it provides a solution for managing extensive datasets and long-term process analysis.
  • Sales execution/pricing: Timeline is priced in three tiers based on the number of Timeline projects, or containers for data being analyzed: 5, 15 and 25. The number of users is unrestricted. Customers deploying on-premises or via their private cloud see no pricing or licensing differences.

  Cons:

  • Market understanding: Compared to other vendors assessed in this Magic Quadrant, ABBYY is behind the innovation curve in a rapidly evolving process mining market. For instance, the platform's assessed release did not include GenAI capabilities, and its roadmap is aligned more toward its existing customer base to promote process mining as an enabler for its core intelligent document processing (IdP) offering. This creates a barrier for clients looking for a platform of choice for general-purpose process mining.
  • Marketing execution: ABBYY is not aggressive as the MQ leaders in promoting its process mining offering. Its investment in marketing, developer communities and partner networks is smaller compared to competitors of similar size, which could explain its lower market share. This limited visibility and awareness might impact end users by potentially limiting community support and integrations.
  • Process orchestration: ABBYY focuses on the automation aspect of executing processes, rather than the broader orchestration of processes, which involves designing and managing the interdependencies between different processes. This approach also affects its capabilities in object-centric process mining (OCPM), which requires orchestration to analyze and optimize the interactions between various process elements. Clients that need sophisticated orchestration and OCPM features should verify that ABBYY's offerings align with their specific requirements.


• Appian - Challenger
  

  Pros:

  • Market responsiveness: Appian sources ideas from its large community, engaging with users in a variety of settings, from local forums to larger events. Appian has a strong improvement cycle that enables it to move from concept to general availability, supporting customers' needs and remaining competitive as the market evolves.
  • Geographic strategy: Appian has internal offices and an extensive partner network to support process mining customers globally. Appian provides direct sales, services and support worldwide, and their sales strategy is tailored to the different markets they serve.
  • Product strategy: Appian's data fabric serves as the basis for analyzing data with Process HQ for implementations on the Appian platform. It captures and prepares data, offering connections to external systems and creating knowledge data models. Data fabric offers a unified data layer for heterogeneous IT landscapes, providing data access for process analysis.

  Cons:

  • Marketing execution: Appian focuses on process mining for process optimization more than process discovery. It primarily uses process mining as an enabler for its wider platform and focuses on using process mining to monitor and optimize currently automated processes on its platform. This creates a barrier for clients looking for a platform of choice for general-purpose process mining.
  • Sales strategy: Appian's sales strategy primarily targets large enterprises with revenues exceeding $1 billion. End users from smaller businesses should be aware that the company's focus might lead to different levels of engagement or customization, compared to larger clients.
  • Sales execution/pricing: Appian bundles Process HQ with the Appian platform and directs clients toward its cloud offering, reviewing requests for on-premises deployment on a case-by-case basis.


• Microsoft - Challenger
  

  Pros:

  • Product strategy: Power Automate Process Mining integrates the GPT-4o mini model. Optimized for real-time and background processing, it enables Power Automate Copilot function chaining for handling complex workflows. This helps end users uncover processes from their data, map to required schemas and gain insights through conversational AI.
  • Vertical strategy: Microsoft has wide geographic and industry coverage, with an extensive partner ecosystem. It also offers industry-specific solutions and services that use the entire breadth of the Microsoft ecosystem.
  • Sales execution: Microsoft has aligned Power Automate Process Mining with the company's overall go-to-market approach. It has done so by deeply integrating the offering with Microsoft technologies such as Azure, Dataverse, Power Automate and Power Apps. This integration benefits end users by providing a connected experience within the Microsoft ecosystem, enabling cohesive data management.

  Cons:

  • Market responsiveness: Despite OCPM being on the roadmap for two years, we still do not see it in Microsoft's product. However, the company is currently using an alternative approach, involving AI-driven guidance for intelligent data selection, analysis and accessibility for business users, to help customers understand processes across multiple objects.
  • Deployment models: Following the acquisition and full integration of Minit into the Microsoft ecosystem, Power Automate Process Mining cannot be deployed on-premises. This makes it unsuitable for those required to keep their data in-house and may also make it unsuitable for those in highly regulated industries.
  • Sales strategy: Microsoft's accelerators focus more on Microsoft-related use cases. This is reflected by its sales channels mainly focusing on existing Microsoft customers. Clients considering use cases other than Microsoft-related ones should check the experience level, available connectors and support that Microsoft and its implementation partners deliver.


• ServiceNow - Challenger
  

  Pros:

  • Marketing execution: ServiceNow demonstrates strong execution by leveraging its ecosystem and established presence in the enterprise software market. It capitalizes on its strong brand reputation and existing customer relationships to drive the adoption of its process mining solutions.
  • Customer experience: Ease of use has been quoted as a strength for the ServiceNow platform by our end users in their interactions with us. Initiatives such as Guided Setup have significantly reduced the time it takes for end users to gain process insights.
  • Product strategy: For a relatively new entrant to this market, ServiceNow has a well-rounded set of process mining capabilities. These capabilities include multidimensional mining, integration with performance analytics for real-time KPI monitoring, and the use of GenAI for process insights.

  Cons:

  • Product strategy: ServiceNow offers process mining as an extension of its main product. While ServiceNow Process Mining is available as a stand-alone product, it is not frequently shortlisted as such. This suggests that buyers seeking a dedicated, stand-alone process mining tool may find ServiceNow's product strategy is more focused on integration within its ecosystem, rather than independent deployment.
  • Sales execution/pricing: Licensing costs and complexity can be a concern, despite ServiceNow's new licensing model that allows mining of any business process (both native and external to the ServiceNow platform) with a single SKU. Different licensing terms may apply, depending on contract specifics (enterprise or otherwise). Those who do not use the ServiceNow platform should verify their pricing and usage metrics with ServiceNow.
  • Customizations and setup: ServiceNow Process Mining has fewer assets for non-IT service management use cases and lacks depth in third-party workflow, according to clients in conversations with us. ETL is not as simple in the stand-alone offering, so prospective customers who do not use the ServiceNow platform should verify ETL capabilities during the proof-of-concept stage.


• QPR Software - Visionary
  

  Pros:

  • Product strategy: QPR now delivers QPR ProcessAnalyzer as a Snowflake Native App and uses GenAI in its synthetic data mode to predict event logs. QPR brings process mining to the source of data and this helps end users quickly get to process insights. It has also introduced process simulation that uses AI to automatically identify the used resources from a standard event log, and has added a native OCPM flowchart visualization to its object-centric back end, enabling visualization of different processes in one view.
  • Market positioning: QPR clearly communicates its first-mover and differentiating positioning in delivering QPR ProcessAnalyzer as a Snowflake Native App. This approach brings the use cases and related workloads to where the data is, instead of copying data to a stand-alone island for process mining. The solution offers off-the-shelf scalability, data security and one-click deployment, expediting value creation.
  • Operations: QPR's on-premises product has the same functionalities as other deployment modes. For end users who need to deploy process mining on-premises, QPR offers a viable option.

  Cons:

  • Sales strategy: QPR's sales strategy focuses mostly on Snowflake customers, Snowflake customers with other process mining tools, midsize companies in the Nordics, and banks and financial services companies in Saudi Arabia. Prospect customers with varied data sources and in different geographies should check their requirements with QPR.
  • Geography: QPR is not a market newcomer, but its geographic presence is limited. Its sales offices are in Finland and soon will be in Saudi Arabia. Prospective customers should confirm the vendor's support in their specific operating regions.
  • Customer experience: QPR and its offering have seen many changes over time, so prospects should ask QPR for relevant user experiences when assessing the product. Execution through automation is basic. Potential clients should check whether QPR meets their requirements for advanced capabilities.


• Decisions - Niche Player
  

  Pros:

  • Sales execution/pricing: Decisions offers a relatively simple pricing structure with an annual SaaS model that imposes no minimums or maximums on users, processes or cases. The minimum contract term is 12 months, and on-premises implementations are discounted.
  • Marketing execution: Decisions' product and go-to-market strategy focuses on case management in the business process automation (BPA) market. Decisions has released a beta version of its product (CaseSpark 2.0) that will combine process mining and case-based workflows via event log inspection. It works by generating additional prebuilt forms and rules via metadata extraction to make automation of an existing process easier.
  • Marketing strategy: Decisions markets its process mining capabilities by highlighting features like 'one-click instant insight analysis' and tools such as the cost analyzer and process simulator. This includes targeted messaging by persona and vertical, driven by Decisions as well as their partners.

  Cons:

  • Market understanding: Decisions focus more on automation use cases (improving process automation by discovering and validating automation opportunities) than the other three use cases being assessed.
  • Geographic strategy: Decisions has a strong geographical focus on North America. The bulk of their employees are in North America, and they rely on their partners for EMEA and Latin America. Prospects in regions other than North America should verify levels of coverage with Decisions and their partners.
  • Market understanding: Decisions does not have a native task mining capability and offers task mining integration through strategic partnerships. While native task mining capability is in their roadmap for 2025, prospective customers should check directly with Decisions on the availability.


• iGrafx - Niche Player
  

  Pros:

  • Customer experience: iGrafx has received good ratings for satisfaction and ease of product use on Gartner Peer Insights. To enable adoption, it offers iGrafx University (iGU), a web-based education platform that combines free and paid training programs designed for practitioners, customers and partners.
  • Marketing execution: iGrafx targets several personas, including beginner and advanced process excellence professionals, transformation heads, line-of-business leaders and risk/compliance professionals. Messaging is tailored to each role, emphasizing benefits such as improved productivity, cost reduction, compliance and risk mitigation.
  • Product innovation: iGrafx's core innovation features include GenAI-powered Pia for process discovery via natural language, enhanced AI-based predictive analytics and integration of process mining with simulation.

  Cons:

  • Market responsiveness: iGrafx does not support OCPM. This limits the tool more than traditional process mining, because OCPM broadens the way data is collected and processed, enabling users to see events and objects in all their states along different processes.
  • Product strategy: iGrafx's focus on broader process intelligence means the platform lacks some process mining capabilities that others offer. For example, it does not offer any accelerators or templates for industry verticals or targeted use cases that are common with other participating vendors.
  • Geographic operations: iGrafx lacks the size and scale of other vendors in this research, and relies on its partners in different regions for sales and implementations. For instance, it leverages its partnership with NTT DATA INTRAMART in Asia/Pacific. Prospective buyers should check with iGrafx and its partners to ensure there is adequate resource coverage in their region.


• Proxverse - Niche Player
  

  Pros:

  • Innovation: Proxverse is incorporating AI-driven innovation, using LLM capabilities for autonomous process diagnosis, intelligent diagnostics and optimization reporting. Self-customized LLM-based process diagnosis enables users to tailor prompts for LLM-generated process analysis. Proxverse also emphasizes customer-centric collaboration through workshops and feedback-driven development cycles.
  • Geographic strategy: Proxverse targets the Chinese market, which is one of the fastest growing process mining markets. It offers adherence to local data protection laws, a feature not offered by other vendors. This is important for end users based in China. The company works with major clients in banking, manufacturing and telecommunications. It also provides customized pricing packages to meet local industry budgets and ROI expectations.
  • Marketing execution in China: Proxverse has a team of industry experts and offers its expertise through webinars and workshops, benefiting end users by offering insights and guidance tailored to specific industries.

  Cons:

  • Business model: Proxverse's specific focus on China limits its growth in other markets. Prospective customers outside China should confirm the vendor's support in their specific operating regions as the vendor expands its geographical scope.
  • Sales execution: Proxverse is still a small vendor, although it is growing steadily and partners with consulting and systems integrators. Its close involvement with its clients in installation, implementation, close support, troubleshooting, consulting, training, customizations, integrations and execution impacts scalability.
  • Product strategy: The product still lacks some critical and advanced functionality in the current product offering, contributing to a relatively lower assessment of its ability to execute. Proxverse has no task mining capabilities and very basic process orchestration capabilities. Potential clients that need some advanced process mining capabilities should check that Proxverse can meet those requirements.

Reference

• Gartner, Magic Quadrant for Process Mining Platforms, 15 April 2025, ID G00816659

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