Magic Quadrant for Process Mining Platforms
ARCHIVED
15 April 2025 - ID G00816659 - 61 min readBy Tushar Srivastava, Marc Kerremans, and 1 more
Process mining platforms give enterprise application leaders visibility and insights into their business processes and application landscapes, enabling them to make smarter decisions aligned to their organization’s priorities. We examine market forces and the leading vendors of platforms.
Market Definition/Description
Process mining platforms offer comprehensive analysis of end-to-end processes by extracting event data from information systems. This includes automated process discovery (extracting process models from an event log), conformance checking (monitoring deviations by comparing model and log), social network/organizational mining, automated construction of simulation models, model extension, model repair, case prediction and history-based recommendations. Process mining platforms extend process mining capabilities via advanced process analytics, process improvement detection and process improvement recommendations.
- Process discovery and analysis — Process mining provides visibility and understanding of actual business operations and processes, resulting in unbiased, adaptable and maintainable process models. This extends to providing targeted insights on improving business operations and outcomes. Process mining enables business process analysts to create an updated business process repository that is used to analyze, streamline and redesign complex processes.
- Process conformance — Process mining helps validate or audit whether actual execution of business processes are in conformance with internally defined compliance protocols, policies and best practices baked into enterprise applications, such as ERP and CRM. It also ensures the reliability of external financial reporting and compliance with external laws and regulations. Another variation of this use case is the comparison and analysis of the same processes across different business units, subsidiaries or even countries (comparative process mining).
- Enterprise application modernization — Process mining enables enterprises to assess the impact of application modernization by uncovering the true state of operations. It provides insights into how changes in one application can create ripple effects throughout the application landscape. By visualizing interdependencies and identifying bottlenecks, process mining enables decision makers to understand the broader implications of modernization efforts, ensuring that updates lead to enhanced efficiency, reduced risks and alignment with strategic business goals.
- Discovering and validating automation opportunities — Process mining helps business analysts discover and assess the opportunities for process automation. It effectively creates the business case for automation, which is difficult without actual process context. Process models are often used to configure enterprise applications and their integrated processes, such as ERP and CRM.
- Digital transformation — After shifting the scope of process mining to the operational and organizational level, it is a small step to link these operational insights to big strategic initiatives like digital transformation or digital business. This growing use case is getting more attention because of the theme of digital business and, more recently, digital transformation.
- Discovering and validating agentic AI opportunities — As business processes are unique to enterprises, generic agentic AI capabilities would neither be scalable nor maintainable. Process mining enables enterprises to create and validate their custom agentic AI requirements against their true state of business operations.
Mandatory Features
The mandatory features for this market include:
- Event log extraction — Involves connecting with and extracting event logs from source systems on which business processes run (independent from task mining). The platform should offer robust extraction, transformation and loading (ETL) capabilities to ensure that data is efficiently processed and transformed into a format suitable for analysis.
- Process models and analysis — Involves automated discovery of process models, exceptions and process instances (mostly referred to as “cases”), client interactions (journeys), and employee interactions, together with basic frequencies and statistics from event logs.
- Comparative process mining — Includes capabilities to check conformance and compliance, not only graphically through overlays, but also through data analysis and performing gap analysis.
- Process model enhancement — Involves intelligent support for enhancing or extending existing or a priori process models by using additional data from recorded logs and events.
Common Features
The common features for this market include:
- Process orchestration — A platform that extends the process mining capabilities across different processes with advanced analytics capabilities and decision management capabilities. The platform also offers APIs to create process mining apps. This allows organizations and partners of process mining vendors to create applications such as financial auditing tools.
- GenAI capabilities — Involves using GenAI-powered capabilities to improve data preprocessing and discovery; supporting adaptive process modifications through real-time monitoring and refined recommendations; and enhancing explainability and understandability, thus broadening process mining accessibility to a wider audience.
- Execution support — Involves execution capabilities that turn insights into action. These capabilities could range from simply updating source applications (applications that deliver the events for process mining) to preparing or creating scripts that support the execution of tasks or processes.
- Data access and preparation — Includes data preparation, data quality and data integration, supporting big data as well as different ways to handle data.
- Business activity monitoring and management — Real-time dashboards with support for KPIs that are continuously monitored and enable decision support.
- Advanced process analysis — Involves predictive analysis, prescriptive analysis, scenario testing, simulation and advanced process analytics capabilities that use contextual data.
- Task mining — Involves inferring useful information from low-level event data available in UI logs. The UI logs describe the single steps within a task done by a user, such as using a workstation based on keystrokes, mouse clicks and data entries.
Magic Quadrant
Vendor Strengths and Cautions
ABBYY
ABBYY is a Challenger in this Magic Quadrant. The process mining offering we assessed is ABBYY Timeline, version 6.13. It is sold as a stand-alone product and also sold as a private-labeled product by SS&C Blue Prism under the name Blue Prism Process Intelligence. ABBYY can be delivered via SaaS and on-premises.
ABBYY offers predictive modeling, integration capabilities through public APIs and multimodal models for image and text analysis, supporting integrated process and task mining.
ABBYY operates globally, with most resources in the U.S. and Europe. ABBYY serves verticals including banking, financial services and insurance (BFSI); manufacturing, finance and accounting (horizontal); and pharmaceuticals.
In 2025, ABBYY plans to enhance event handling for better tracking and analytics. It also plans to improve workflows and analytics into actionable insights, with self-optimizing automation augmented with agentic-based task completion.
- 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.
- 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
Appian is a Challenger in this Magic Quadrant. The process mining offering we assessed is Process HQ, platform version 24.4. It is sold as a bundle with the Appian platform, as well as stand-alone. Appian can be delivered via SaaS and on-premises.
Appian operates globally, focusing on clients in North America, EMEA and Asia/Pacific, with strengths in the public sector, finance, insurance, life sciences and telecommunications.
Since its acquisition of Lana Labs in 2021, it has enhanced its wider platform to support clients undergoing full-automation life cycles, from application design and workflow automation to continuous improvement and optimization.
In 2025, Appian aims to integrate Process HQ with its GenAI offering for enhanced process analysis and optimal workflows. It also plans to develop no-code templates to streamline process discovery for enterprise systems.
- 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.
- 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.
Apromore
Apromore is a Leader in this Magic Quadrant. The process mining offering we assessed is Apromore Enterprise Edition 10.1. Apromore’s process mining is accessible on cloud via annual subscriptions. Apromore does not offer on-premises deployment.
Apromore is system-agnostic and supports multidimensional tagging of events. Apromore’s predictive analytics features enable end users to train machine learning (ML) models to predict remaining time, deadline violations and case outcomes.
Apromore has offices in Australia and the U.S. It supports industries like BFSI, healthcare, manufacturing and energy.
In 2025, Apromore plans to innovate with GenAI by using large language models (LLMs) to provide contextualized answers to process discovery, redesign and simulation questions.
- 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.
- 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)
ARIS is a Leader in this Magic Quadrant. The process mining offering we assessed is ARIS Process Mining, version 10 SR27. It can be delivered via SaaS and on-premises.
ARIS operates primarily in North America and EMEA. It focuses on BFSI, retail, manufacturing, government and healthcare.
It offers prescriptive analytics to define actionable rules and decisions based on findings. The platform uses heuristic approaches for early warnings on KPI deviations and supports decision modeling with decision modeling notation (DMN) for rule checks. ARIS Process Mining also offers prebuilt accelerators for various processes.
In 2025, ARIS plans to add autonomous insights, an AI workbench and improved simulation for process efficiency.
- 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.
- 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
Celonis is a Leader in this Magic Quadrant. The process mining offering we assessed is Celonis Process Intelligence Platform. Celonis is delivered mainly as SaaS via public multitenant and private single-tenant clouds. A nonstandard on-premises option is available in specific circumstances.
Celonis Platform includes Celocore and OCPM. Celocore, the Celonis data stack, offers process mining at scale as data volumes increase. OCPM provides a comprehensive view of business operations.
It services its global customers from 22 offices in EMEA, North America, Latin America and Asia/Pacific. Its clients span all industries.
In 2025, Celonis aims to increase its presence in India, plans to continue integrating AI, expand OCPM capabilities, integrate its orchestration engine, and enhance its low-code process intelligence app-building user experience.
- 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.
- 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.
Decisions
Decisions is a Niche Player in this Magic Quadrant. The process mining offering we assessed is Decisions Process Mining, version 3.3. Decisions can be delivered via SaaS and on-premises.
Decisions operates primarily in the United States and Asia/Pacific. Decisions serves verticals including finance, healthcare, insurance and manufacturing.
Decisions offers built-in process mining and capabilities such as comparative process mining, process mapping and analysis. It enables end users to capture process execution data to identify inefficiencies, bottlenecks and process optimization opportunities.
In 2025, Decisions plans to introduce GenAI capabilities that support natural language queries, and expression syntax capabilities for filtering and aggregation functions. It also plans an enhanced connection to case-based workflow automation, as well as a custom dashboard API and task-mining capabilities.
- 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.
- 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.
IBM
IBM is a Leader in this Magic Quadrant. The process mining offering we assessed is IBM Process Mining, version 2.0.0. It can be deployed via Red Hat OpenShift, which supports both on-premises and cloud environments, as well as through SaaS and on-premises options via IBM Cloud Paks.
IBM has a large global presence and it targets industries such as BFSI, IT services, energy and utilities, retail, manufacturing, and pharmaceuticals.
IBM Process Mining supports OCPM. It offers a data-driven approach with prescriptive AI for actionable insights and integrates with IBM’s watsonx platform.
In 2025, IBM plans to integrate watsonx.data and build a specialized LLM for use-case and vertical solutions to enhance analysis with a causal explanation algorithm and extend cross-process capabilities.
- 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.
- 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.
iGrafx
iGrafx is a Niche Player in this Magic Quadrant. The process mining offering we assessed is iGrafx Process360 Live, version 19.5. iGrafx is accessible on cloud and on-premises.
iGrafx operates mainly in the U.S. and Europe, focusing on clients in BFSI, healthcare and manufacturing.
It offers a process intelligence platform with bundled process mining, design and optimization capabilities. It uses predictive analytics to forecast task completion and detect noncompliance. The platform also offers GenAI capabilities through its Process Intelligence Assistant (Pia) to enhance process mining.
In 2025, it plans to enhance persona-based UX, predictive analysis and root cause enhancements, launch an application builder framework, and make improvements to Pia.
- 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.
- 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.
MEHRWERK
MEHRWERK is a Leader in this Magic Quadrant. The process mining offering we assessed is mpmX Process Excellence Platform, version 2.5. mpmX can be delivered via SaaS and on-premises.
MEHRWERK operates mainly in Europe, targeting sectors like the industrial and automotive industries. They also focus on insurance, logistics, manufacturing and the public sector.
MEHRWERK combines business intelligence (BI) software and services with process mining technology. Its open-platform approach makes mpmX compatible with many BI stacks.
In 2025, MEHRWERK plans to enhance its open-platform approach, extending solution marketplaces for value realization by using data ecosystems, such as bringing the mpmX platform live on Databricks.
- 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.
- 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.
Microsoft
Microsoft is a Challenger in this Magic Quadrant. The process mining offering we assessed is Microsoft Power Automate Process Mining. It is deployed via Microsoft Azure and is not available on-premises.
Microsoft operates globally and for its process mining offering, it focuses on telecommunications, automotive/manufacturing, retail, insurance and healthcare.
Power Automate Process Mining operates on Microsoft’s low-code platform, covering task mining, robotic process automation (RPA) and IdP. It offers prebuilt templates and aligns with frameworks like Six Sigma’s “define, measure, analyze, improve and control” (DMAIC).
In 2025, it plans to continue AI innovations and Microsoft Copilot investments, support Microsoft Fabric, and enhance end-to-end automation observability.
- 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.
- 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.
Pegasystems
Pegasystems is a Leader in this Magic Quadrant. The process mining offering assessed is version 24.2, combined with Pega Workforce Intelligence 8.8.4 and Pega Platform 24.2. Pega can be delivered only as a cloud offering.
Pegasystems’ operations are geographically spread, with most resources in the U.S. It supports clients in all industries with a focus on financial services, healthcare, manufacturing and government.
Its process mining integrates with Pega GenAI Blueprint, enabling users to generate new Blueprints directly from the captured process data. It also integrates prebuilt text mining features to derive business insights, and uses IdP and OCR for deeper analysis.
In 2025, Pega plans to introduce headless process mining, GenAI agents that help streamline data acquisition and analysis, offer OCPM capabilities, and extend the integration between process and task mining with Pega Blueprint.
- 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.
- 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.
Proxverse
Proxverse is a Niche Player in this Magic Quadrant. The process mining offering we assessed is Proxverse Studio, version 3.17. Proxverse Studio can be delivered via SaaS and on-premises.
Proxverse operates mainly in China, with clients in banking, manufacturing and telecommunications.
Proxverse Studio features Data Fusion (extraction, transformation and loading [ETL]), process mining and analysis, process management, and low-code automation. It integrates GenAI for natural language queries and process query language. It offers software development kits and APIs to integrate process mining into other applications.
In 2025, Proxverse plans on enhancing its platform with AI, including a customized LLM assistant, AI agents for execution and customizable process simulation.
- 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.
- 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.
QPR Software
QPR Software is a Visionary in this Magic Quadrant. The process mining offering we assessed is QPR ProcessAnalyzer, version 2024.7. It can be deployed on-premises, in a private cloud, as a SaaS solution, or as a Snowflake Native Application.
QPR operates mainly in Finland, but has expanded into the U.S. It serves clients in Europe, the Middle East and the U.S., in sectors such as pharmaceuticals, manufacturing, banking and telecom.
QPR offers one-click root cause analysis, clustering analyses and machine learning predictions.
In 2025, QPR plans to enhance agentic AI, extend OCPM support, improve interoperability and add dynamic visualizations.
- 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.
- 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.
SAP Signavio
SAP Signavio is a Leader in this Magic Quadrant. The process mining offerings we assessed are SAP Signavio Process Intelligence and SAP Signavio Process Insights, version 17.4. Both are components of the SAP Signavio Process Transformation Suite R24Q3.5. It is a cloud-native SaaS application on the public cloud, with connectivity to on-premises data sources, and offers a managed private cloud option.
Its operations are geographically diverse, and it serves clients across all industries.
It offers process mining, analysis, insights and root cause analysis, focusing on insights to action with AI-assisted capabilities.
In 2025, SAP Signavio plans to introduce AI-assisted conformance for event logs, case modeling with object-centric visual definitions, an AI-assisted process modeler, and integrated content from Process Insights and Process Intelligence.
- 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.
- 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.
ServiceNow
ServiceNow is a Challenger in this Magic Quadrant. The process mining offering we assessed is ServiceNow Process Mining, version Xanadu. ServiceNow can be delivered via SaaS and on-premises.
ServiceNow operates globally and has a presence across all industries.
It offers advanced analytics such as predictive, prescriptive and root cause analyses, with native integration into the ServiceNow platform. The offering is available as an extension to the core ServiceNow platform and as a stand-alone solution.
In 2025, ServiceNow plans to innovate with GenAI for summarization and process generation, integrate agentic AI, and replatform its acquisition of UltimateSuite to provide task mining capabilities for better workflow insights.
- 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.
- 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.
UiPath
UiPath is a Leader in this Magic Quadrant. The process mining offerings we assessed are UiPath Process Mining, Task Mining and Communications Mining, version 2024.10. It can be delivered via SaaS and on-premises.
UiPath operates globally, focusing on North America and EMEA. It serves clients in all industries, including financial services, manufacturing, healthcare and government sectors.
UiPath offers visual process graphs, KPIs and GenAI-powered assistance for analysis. It integrates task and communications mining, offering predictive analytics, automation triggers and process intelligence with business rules and alerts.
In 2025, UiPath plans to expand its library of prebuilt solutions to accelerate time to value, especially for industry-specific use cases.
- 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.
- 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.
Vendors Added and Dropped
We review and adjust our inclusion criteria for Magic Quadrants as markets change. As a result of these adjustments, the mix of vendors in any Magic Quadrant may change over time. A vendor's appearance in a Magic Quadrant one year and not the next does not necessarily indicate that we have changed our opinion of that vendor. It may be a reflection of a change in the market and, therefore, changed evaluation criteria, or of a change of focus by that vendor.
Added
- Decisions
- iGrafx
- ServiceNow
Dropped
The following vendors were dropped as they did not fulfill one or more inclusion criteria decided by Gartner:
- Cyclone Robotics: The vendor was dropped because the vendor does not meet the technical and business criteria.
- mindzie: The vendor was dropped because the vendor does not meet the business and size criteria.
- Skan: The vendor was dropped because the vendor does not meet the technical criteria.
- StereoLOGIC: The vendor was dropped because the vendor does not meet the technical criteria.
- UpFlux: The vendor was dropped because the vendor does not meet the technical and business criteria.
Inclusion and Exclusion Criteria
To qualify for inclusion in this Magic Quadrant, each vendor had to meet the following criteria:
Technical criteria:
- A provider must demonstrate active participation in the process mining market and meet the Gartner definition for the process mining market, including the characteristics listed in the definition’s Purpose Summary, Mandatory Features and Common Features sections.
- A provider must conclusively demonstrate that they offer comprehensive process analysis through the ingestion of event data, which involves capturing and processing data from various source systems where business processes are executed. While task mining and screen recording can be optional capabilities of the platform, they should not be the primary or sole methods for process analysis. Vendors that predominantly rely on task mining techniques for process analysis, such as screen recording or related techniques, are excluded from consideration.
In addition to the above market and technical criteria, each participating vendor must meet the following business and size criteria:
The vendor had to have realized one of the following in 2023:
- Audited/reported annual tool licensing revenue of over $7 million
- Audited/reported annual tool licensing revenue of over $3.5 million and at least 40% year-over-year growth
- Audited/reported annual tool licensing revenue of over $3.5 million and at least 15 net-new logos in 2023
The vendor must have a customer interest index (CII) score of at least 50 or above.
For this 2024 Magic Quadrant, Gartner has internally calculated a CII score with a maximum value of 100, based on a combination of multiple factors, such as:
- Gartner inquiry volume
- Gartner.com Peer Insights
- Social media followers
- Gartner.com search trends
- Internet search trends
- Web traffic analysis
International presence: The vendor must have had active customers buying process mining tools in the 12 months preceding the start of this research, in at least two of the following major global regions: EMEA, Asia/Pacific, North America and South America.
Exclusion criteria:
- Predominantly relying on task mining methods, including screen capture or similar techniques, for conducting process analysis.
Honorable Mentions
The following vendors are not included in this research because they do not meet one or more of the inclusion criteria. All are active in the process mining market and sometimes compete against the vendors covered in this Magic Quadrant:
- AlphaFlow Technologies — Vendor specializing in process automation, orchestration, analysis and process mining, primarily serving the Chinese market.
- Arkturus Business Research — Vendor that provides process mining predominantly in New Zealand and Australia.
- Datricks — Vendor that focuses on auditing and compliance, risk management and process governance.
- DCR Solutions — A vendor providing process mining and digitization solutions for heavily regulated industries, focusing on process compliance and transparency.
- Fluxicon — Vendor of Disco, a popular stand-alone, analysis-focused process mining tool.
- inverbis — Vendor that has been incubated by the Universidade de Santiago de Compostela in Spain and offers a process mining platform.
- mindzie — mindzie is a provider of process mining, task mining and process modeling to midenterprise and enterprise customers in North America, South America, Middle East, Europe and Asia/Pacific.
- process.science — Vendor that delivers process mining on top of BI platforms, such as Power BI, Qlik Sense and Tableau. Vendor repackages their product to other process intelligence vendors in the market.
- PuzzleData — Vendor offering process mining solutions in Korea, specializing in finance transformation, customer journey analysis, and manufacturing optimization.
- UpFlux — Vendor offering a process mining platform in South America, combining process mining, AI, automation and expert services to enhance performance monitoring, decision making and digital transformation.
Evaluation Criteria
In Magic Quadrants, Gartner positions vendors on two axes: Ability to Execute and Completeness of Vision. These axes reflect numerous criteria that measure each vendor’s performance and its future vision. Vendors receive evaluations based on Gartner’s methodology for Magic Quadrants. Vendors are invited to provide data for the evaluation criteria via questionnaires and briefings, but evaluations also reflect the results of Gartner customer insights and information gathered from client inquiries.
Ability to Execute
We evaluated the vendors’ Ability to Execute in the process mining platforms market by using the following dimensions and criteria.
Product or Service: We assessed what the vendor’s process mining offering delivers to process mining practitioners and how it does so. These offerings may be packaged as a single product, multiple products, a platform or, in many cases, stand-alone products that are also bundled as a component in a broader platform. In the case of broader platforms, we assessed only the process mining component and mentioned the opportunities to connect to other components of the platform. We assessed current capabilities, quality and feature sets, as defined in the Market Definition/Description section. Vendors may offer these capabilities natively or through agreements/partnerships with OEMs. Our product assessments explore how well the products meet the core and tangential capabilities and support the use cases.
Overall Viability: We assessed the organization’s overall financial health and the business unit’s financial and practical success. We also assessed the likelihood that the organization would continue to offer and invest in the product, as well as advance the product’s position within the organizational product portfolio. We looked at all forms of growth, including organic growth, as well as acquisitions and the securing of additional funding. We valued organic growth more highly than other types of growth.
Sales Execution/Pricing: We assessed the vendor’s sales execution, including presales activities and the structure that supports them. We included responsiveness in sales engagement, deal size and management, pricing and negotiation, presales support, scalability, and the overall effectiveness of the sales channel. We also assessed the clarity of the vendor’s pricing.
Market Responsiveness and Track Record: We considered the vendor’s history of responsiveness to customer requests and changing market needs, including its overall track record in the field. We gave high scores to vendors that were able to respond quickly and change development and/or company direction to meet the needs of an evolving marketplace.
Marketing Execution: We assessed the vendor’s programs, campaigns and events designed to deliver its message to influence the market, promote the brand and business, increase product awareness, and establish a positive identification with the product/brand and organization in customers’ minds. We assessed these programs for their clarity, quality, creativity and efficacy.
Customer Experience: We sought evidence of how products and services enabled customers to achieve anticipated results. We gave high marks for an excellent track record of successful implementations. We looked for clearly articulated mechanisms for ensuring customer success and support for customers, and at what cost. We examined organizational responsiveness, the availability of user groups and service-level agreements. We also factored in customers’ experiences doing business with the vendor and their perceptions of the organization.
Operations: We evaluated the vendor’s ability to meet its goals and commitments. We considered the quality of the organizational structure (such as skills, experiences, programs, systems, applicable standards, the underlying infrastructure, and other vehicles that enable effective and efficient operations).
Ability to Execute Evaluation Criteria
| Evaluation Criteria | Weighting |
|---|---|
Product or Service | High |
Overall Viability | High |
Sales Execution/Pricing | Medium |
Market Responsiveness/Record | Medium |
Marketing Execution | Medium |
Customer Experience | High |
Operations | Low |
Source: Gartner (April 2025)
Completeness of Vision
We evaluated the vendors’ Completeness of Vision in the process mining platforms market by using the following dimensions and criteria.
Market Understanding: We evaluated each vendor’s understanding of customer needs and how it translated that into products and services. We looked for vendors to demonstrate a clear vision of their market. We also assessed how they listened for and understood their customers’ underlying needs, and how they used that understanding to shape or enhance the market.
Marketing Strategy: We sought clear, differentiated messaging that the vendor consistently communicated internally and externalized through its website, social media, advertising, customer programs and positioning statements. We included differentiating strategy based on regions, specific countries and buyer personas, and ways to measure and adapt the strategy.
Sales Strategy: We wanted to understand the vendor’s sales strategy and how it used direct and indirect sales, marketing, service and communication. We also examined the vendor’s use of, and reliance on, partners to extend its scope and reach, focusing on the levels of expertise and technology required, as well as the partners’ services and customer base. We also included target customer personas and sales strategies differentiated for the vendor’s context, size, level of maturity and geographic locations.
Offering (Product) Strategy: We explored the vendor’s approach to developing a compelling product and service vision, with an emphasis on market differentiation, functionality, methodology and features as they mapped to current and future requirements.
Business Model: We assessed the design, logic and execution of the vendor’s business proposition to achieve continued success. We explored support for customers in different deployment modes, the vendor’s business capabilities, its overall value propositions, related profit models and the resources at its disposal.
Vertical/Industry Strategy: We assessed the vendor’s strategy to direct resources (sales, product and development), skills and offerings to meet the specific needs of individual industry segments. We examined any focus on particular industry verticals and associated standards, and revenue performance in the vendor’s top sectors.
Innovation: We explored the vendor’s innovation vision, examining its resources, expertise and capital for investment. We looked for a strong product vision that pushed the market forward, while considering the disruptive and opportunistic forces of digital on businesses. We also considered the vendor’s ideas for innovation and market development.
Geographic Strategy: We examined the vendor’s strategy to direct resources, skills and offerings to meet the specific needs of geographies outside its “home” geography, either directly or through partners, channels and subsidiaries, as appropriate for that geography and market.
Completeness of Vision Evaluation Criteria
| Evaluation Criteria | Weighting |
|---|---|
Market Understanding | High |
Marketing Strategy | Medium |
Sales Strategy | Medium |
Offering (Product) Strategy | High |
Business Model | Medium |
Vertical/Industry Strategy | Low |
Innovation | High |
Geographic Strategy | Low |
Source: Gartner (April 2025)
Quadrant Descriptions
Leaders
Leaders have a deep understanding of market realities, a track record of success and an ability to influence the market’s direction, along with an ability to attract and keep a growing customer base.
In the process mining platform market, Leaders understand, facilitate and support diverse use cases (operational excellence, audit and compliance, automation, digital transformation, strategy to execution and customer excellence). Leaders also add other functionality, products and services to core process mining offerings.
Leaders demonstrate a market-leading vision, but also the Ability to Execute on that vision.
A Leader is not always the best choice of vendor. A focused, smaller vendor can provide excellent support and commitment to suit individual needs. Other vendors may provide a certain capability — such as a focus on a particular industry, a better cost-performance ratio, a specific use case, or a commitment to specific features or functions — that is important to an organization. This more-focused type of vendor would not appear as a Leader in the overall process mining tools market. However, within a specific market segment or for a particular use case, it may well be treated as one.
Challengers
Challengers excel in their ability to attract a large user following, but this ability is limited to a subset or segment of the market. For that target audience, Challengers are effectively Leaders, but that specificity presents a barrier to adoption for those outside that subsegment. For instance, in the process mining platform market, a Challenger may have a strong, proven presence or following in the automation segment. However, because of this focus, it may lack sophistication in the evolving use cases or advanced functionality for other use cases in this market.
Alternatively, a Challenger might understand all use cases well and achieve a strong following in its home market, but still struggle to deliver the same levels of success on a global scale.
Although Challengers are typically of significant size with significant financial resources, they may lack elements of the vision we expect, innovative ideas and plans, or an overall understanding of market needs. In some cases, Challengers may offer products that dominate a large, but shrinking, segment of the market. Challengers can become Leaders if their vision develops. Large companies may move between the Challengers and Leaders quadrants as their product cycles and market needs shift.
Visionaries
Visionaries are the innovators driving the market forward by responding to emerging, leading-edge customer demands and by offering new opportunities to excel. Typically, these vendors appeal to leading-edge customers and may even have minimal mainstream presence or name recognition within this market. Their ability to deliver sustained and dependable execution in the mainstream enterprise market is not sufficiently tested or has not yet reached the required level of awareness.
Visionaries can eventually grow to become Leaders. Alternatively, they may decide to limit their target markets to focus on their core competencies, core technologies or existing customers, or excel in a new market and become Niche Players in the process mining platforms market. They could also develop their specialties to advance in execution and become Challengers.
Niche Players
Niche Players operate in a subsegment of a market, or they have a limited ability to innovate or outperform other vendors in the wider market. This limitation may result from a focus on a particular area of functionality, vertical industry or region, or because they are new entrants. Alternatively, Niche Players may struggle to remain relevant in a market that is moving away from them.
Niche Players may have broad functionality, but limited implementation and support capabilities, and relatively limited customer bases. Niche Players can often represent the best choice for a specific category of buyer or for a particular use case. They typically offer specialized expertise, focused support practices, flexible terms and conditions, lower costs, and greater dedication to a particular market segment and its customers.
Some of these vendors have acquired process mining capabilities recently, offer them as stand-alone offerings, and focus on a specific case (e.g., the automation use case), but lack execution because the acquisition was so recent. Other Niche Players target a certain type of process, such as ad hoc, case-based work, and need additional functionality to focus on all process types, or they provide only stand-alone capabilities.
Some Niche Players are poised to improve their Ability to Execute and enterprise features, enabling them to evolve into Challengers. Others will discover innovative solutions that attract interest beyond their niche segments, emerging as Visionaries. Some will strive to strengthen and broaden their businesses to challenge the Leaders. In this fast-evolving and consolidating market, opportunities exist for all.
Context
The process mining solutions included in this research demonstrate successful adoption for business process optimization across all use cases and industry sectors. This signifies mainstream adoption.
Double-digit growth of the process mining market continues, but the main usage patterns — and the role of process mining in the technology portfolio—are evolving. Process mining has transitioned from being a tool for simple process visualization and diagnostics to becoming a critical component in the development of complex, mission-critical business process improvements.
Enterprises prioritize process mining for transformation initiatives that were previously too risky and costly with conventional approaches, and not feasible with standard business process management tools.
Technological advancements — like AI-driven process insights and real-time process optimization — are disrupting traditional business process management methods. Simultaneously, they serve as accelerators for process mining adoption due to the native integration of advanced analytics, monitoring and governance capabilities at the platform level.
Enterprise application leaders should:
- Integrate process mining into their strategy and proactively manage its implementation to prevent organic and uncontrolled expansion of new solutions without adequate planning for architecture governance, budgeting, security and skill management.
- Consider process mining solutions for accelerated adoption of business process automation.
- Educate business stakeholders on innovative methods to enhance processes, including the use of data-driven insights, automated process discovery and, wherever possible, leveraging prebuilt process templates and analytics instead of developing custom solutions from scratch.
Market Overview
Market Size
The process mining market is expanding at a steady pace and is in a high growth phase.
The key drivers continue to be accelerated digital transformation efforts, growing process visibility requirements and increasing demands for business operations resilience.
Worldwide process mining software spending grew by more than 30% in 2024, continuing on its high-growth trajectory from 2023 with a 39.5% growth rate (see Market Share: All Software Markets, Worldwide, 2023). With $871.6 million in revenue in 2023, the market spending is forecast to cross the $2 billion mark by 2028, at a 5-year compound annual growth rate of about 18% from 2023 to 2028.
Market Direction
The process mining market is becoming highly competitive, with successful incumbents expanding their capabilities, a host of new entrants offering niche domain-related process mining solutions, and enterprise software vendors entering the space through acquisitions.
As the understanding of process mining has considerably improved over the past few years, there is increased interest from end users. Gartner’s inquiries on process mining for all of 2023 were surpassed during the first half of 2024.
Process mining’s industry- and object-agnostic nature allows it to be applied in numerous use cases across horizontal and vertical operations. By viewing the technique as “sequencing events based on patterns,” it opens up new possibilities. For instance, tracking clients and their interactions, along with their touchpoints with the organization, transforms process mining into “customer journey mining.”
The focus is on enhancing process discovery and the actionability of insights. Advanced algorithms now automatically map complex workflows, uncover hidden variations and identify inefficiencies with minimal manual intervention. More integration options with enterprise systems and cloud platforms are driving end-to-end process visibility and scalability. Future trends will highlight more GenAI-driven use cases, improved real-time analytics, enhanced user experiences and adaptive process discovery.
Gartner sees five directions in which the process mining platform market will evolve.
Infusion of AI, GenAI and ML
We anticipate more GenAI-driven innovations in the process mining offerings of vendors. Although the core of process mining technology is machine learning rather than GenAI, due to the current hype, vendors will continue to invest in GenAI capabilities, even if some may not be value-accretive.
End users will find many of these capabilities commoditized across vendors, as they are underpinned by similar technology. Innovators and leaders in this market will focus on a mix of AI, ML and GenAI capabilities that generate real business value.
Market Consolidation and Acquisitions
We anticipate further consolidation in this market as smaller vendors, unable to scale operations, become prime acquisition targets. The rapid market growth and strong commitment from enterprises to invest in process mining have significantly heightened interest from private equity investors and major enterprise software vendors. This trend underscores the value and potential of process mining in improving business operations and driving efficiency.
Object-Centric Process Mining
One of the major trends in process mining will be object-centric process mining. OCPM shifts focus from single-case analysis to a multiobject perspective, enabling enterprises to track various entities like customers, products, or services and their interactions within processes. This approach provides a richer view of operations, facilitating deeper insights into complex relationships and dependencies. By integrating object-centric capabilities, process mining platforms can enhance workflow optimization, resource allocation and customer experiences.
Currently, we see an increase in interest from our end users who are mature in their process mining journey. They are likely to benefit from the expanded possibilities offered by the OCPM approach.
Some vendors offer multidimensional mining, which is sometimes misrepresented as OCPM. Multidimension process mining is a different approach that analyzes processes from multiple perspectives, offering broader insights into operations.
Business Operations Intelligence or Operational Intelligence
An extended version of the pure-play process mining market with the critical and tangential capabilities we have mentioned will gradually evolve into a platform for business operations intelligence. This platform will provide a dynamic model of any organization that relies on operational or other data. It will enable the organization to understand how the organization operationalizes its business model, connects with its current state, responds to changes, deploys resources and delivers expected customer value.
This platform will combine all modeling, mapping, mining and monitoring, and support the execution of these models in real-life business operations. Business operations are the combination of processes, interactions and activities that result in products, services and information, and ultimately provide value to the organization’s customers and stakeholders. It will be the implementation of the design pattern that Gartner has, for years, defined as a DTO or a digital twin for business operations.
Specialized/Focused Solutions
We anticipate a continued flow of new entrants, especially for specialized or niche vendors. These vendors will concentrate on vertical solutions, horizontal solutions or specific market segments. Vertical solutions might combine specialized quality processes or external auditing applications. Horizontal solutions could target financial processes or subprocesses within supply chain and logistics. Additionally, specific market segments might focus on small and midsize businesses or offer stand-alone process mining tools.
Market Adoption
Gartner sees five main drivers for the adoption of process mining.
Process Analysis, Optimization and Automation
In these turbulent times, characterized by geopolitical and economic tensions, enterprises are increasingly turning to process optimization and automation to boost efficiency and reduce costs. However, they have realized that without understanding the context of processes and their interdependencies, scaling optimization and automation efforts becomes challenging. Consequently, there is a strong focus on leveraging process mining as a critical tool for dissecting and understanding current workflows. Enterprises are finding significant success in adopting process mining to facilitate ERP modernization, process and task automation, and generate actionable, process-driven insights.
By providing a granular view of operations, process mining empowers organizations to identify inefficiencies, enhance productivity and align processes with business objectives.
Digital Transformation
Digital transformation needs an overhaul in the collaboration between IT, business operations and executive leadership. Enterprises can no longer afford to let these areas operate in isolation. Recognizing this, organizations are increasingly leveraging process mining to enhance business users’ understanding of their processes within the broader enterprise framework. As digital business and transformation become central themes, understanding and optimizing processes is crucial for successfully implementing these initiatives. Process mining serves as an important tool in breaking down silos and fostering a culture of continuous improvement and alignment with digital business objectives.
Artificial Intelligence and Generative AI
The adoption of GenAI in enterprises needs a sound understanding of underlying processes, where process mining plays a key role. Process mining aids in mapping and analyzing workflows, providing insights into process efficiency and bottlenecks. Key aspects include data-driven process discovery, conformance checking and performance analysis. Use cases such as predictive analytics, anomaly detection and process optimization are enhanced by GenAI, which benefits from the granular insights provided by process mining.
Process mining addresses challenges in GenAI adoption by ensuring transparency, compliance and enablement of continuous process improvement through real-time monitoring and adaptive process modifications. These capabilities ensure that GenAI integration is seamless, efficient and aligned with business goals.
Sustainability
Process mining offers comprehensive transparency into business processes. It acts as a digital X-ray for the entire enterprise, uncovering bottlenecks, deviations and compliance issues, while showcasing how ideal processes should look. This not only enhances sustainability objectives by revealing and optimizing operational inefficiencies, but also minimizes resource waste, reducing an organization’s environmental impact through improved process transparency and optimization.
Business Operational Resilience and Autonomous Business Operations
With major changes in business conditions, including but not limited to geopolitical tensions, supply chain issues and broader macroeconomic challenges, it is important for enterprises to have capabilities for becoming operationally resilient.
Operational resilience is a set of techniques that enable people, processes and information systems to adapt to changing patterns. It is the ability to alter operations in the face of changing business conditions. Operationally resilient enterprises have the organizational competencies to ramp up or slow down operations to provide a competitive edge and enable quick and local process modification.
To enable enterprises to adapt, operational resilience uses output from the “sense” and “model” disciplines, and returns information that serves as feedback for improving these activities as well (see Building a Digital Future: Autonomic Business Operations).
The techniques underlying process mining provide a new and enhanced way to encompass the sense and model capabilities. Based on available day-to-day operational data, process mining continuously seeks and finds the relevant objective operational data. The advanced process mining algorithms then provide an accurate model of the organization’s way of working in a format that anyone in the organization can understand. This ensures that everybody can be engaged in the change initiative. Furthermore, it enables continuous adaptation and improvement because, after the change, the new operational data will give insights into the new way of working.
Process Mining Manifesto, IEEE Task Force on Process Mining.
W. van der Aalst, “Process Mining: Data Science in Action,” Springer Verlag, 2016.
W. van der Aalst and J. Carmona (Eds), “Process Mining Handbook,” Springer Verlag, 2022
Ability to Execute
Product/Service: Core goods and services offered by the vendor for the defined market. This includes current product/service capabilities, quality, feature sets, skills and so on, whether offered natively or through OEM agreements/partnerships as defined in the market definition and detailed in the subcriteria.
Overall Viability: Viability includes an assessment of the overall organization's financial health, the financial and practical success of the business unit, and the likelihood that the individual business unit will continue investing in the product, will continue offering the product and will advance the state of the art within the organization's portfolio of products.
Sales Execution/Pricing: The vendor's capabilities in all presales activities and the structure that supports them. This includes deal management, pricing and negotiation, presales support, and the overall effectiveness of the sales channel.
Market Responsiveness/Record: Ability to respond, change direction, be flexible and achieve competitive success as opportunities develop, competitors act, customer needs evolve and market dynamics change. This criterion also considers the vendor's history of responsiveness.
Marketing Execution: The clarity, quality, creativity and efficacy of programs designed to deliver the organization's message to influence the market, promote the brand and business, increase awareness of the products, and establish a positive identification with the product/brand and organization in the minds of buyers. This "mind share" can be driven by a combination of publicity, promotional initiatives, thought leadership, word of mouth and sales activities.
Customer Experience: Relationships, products and services/programs that enable clients to be successful with the products evaluated. Specifically, this includes the ways customers receive technical support or account support. This can also include ancillary tools, customer support programs (and the quality thereof), availability of user groups, service-level agreements and so on.
Operations: The ability of the organization to meet its goals and commitments. Factors include the quality of the organizational structure, including skills, experiences, programs, systems and other vehicles that enable the organization to operate effectively and efficiently on an ongoing basis.
Completeness of Vision
Market Understanding: Ability of the vendor to understand buyers' wants and needs and to translate those into products and services. Vendors that show the highest degree of vision listen to and understand buyers' wants and needs, and can shape or enhance those with their added vision.
Marketing Strategy: A clear, differentiated set of messages consistently communicated throughout the organization and externalized through the website, advertising, customer programs and positioning statements.
Sales Strategy: The strategy for selling products that uses the appropriate network of direct and indirect sales, marketing, service, and communication affiliates that extend the scope and depth of market reach, skills, expertise, technologies, services and the customer base.
Offering (Product) Strategy: The vendor's approach to product development and delivery that emphasizes differentiation, functionality, methodology and feature sets as they map to current and future requirements.
Business Model: The soundness and logic of the vendor's underlying business proposition.
Vertical/Industry Strategy: The vendor's strategy to direct resources, skills and offerings to meet the specific needs of individual market segments, including vertical markets.
Innovation: Direct, related, complementary and synergistic layouts of resources, expertise or capital for investment, consolidation, defensive or pre-emptive purposes.
Geographic Strategy: The vendor's strategy to direct resources, skills and offerings to meet the specific needs of geographies outside the "home" or native geography, either directly or through partners, channels and subsidiaries as appropriate for that geography and market.