The Best Process Mining Tools for 2026 – A Practical Market Overview

Process mining and process intelligence have evolved rapidly in recent years. What once served primarily as an analytical tool for individual ERP processes has become a core component of data-driven enterprise management. Today’s processes are no longer linear or confined to a single system - they span multiple applications, data platforms, and organizational units.

Looking ahead to 2026, one thing is clear: companies no longer use process mining merely for transparency, but as a foundation for informed decision-making, automation, and continuous process improvement. At the same time, the market has become increasingly complex. Many vendors promise similar outcomes, yet differ significantly in architecture, functional scope, cost structures, and user experience.

This article provides a structured overview of the most important process mining tools for 2026 and highlights what organizations should truly focus on when selecting a solution.

Executive Summary for Time-Constrained Readers

In 2026, process mining is a core capability for modern, digitally driven organizations. While the market offers a wide range of tools, they differ substantially in architecture, functionality, and cost. Celonis, SAP Signavio, and UiPath are considered established market leaders, while mpmX positions itself as a data-platform-centric alternative with a strong focus on object-centric process mining (OCPM), scalability, and lower operating costs. Five key criteria are critical when selecting a tool: company size, functional scope, technical integration, budget, and user experience.

What Organizations Should Consider When Selecting a Process Mining Tool

Choosing the right tool should not be driven by market visibility or individual features alone, but by clear, practical criteria. In real-world projects, five aspects have proven particularly decisive.

Company Size and Organizational Maturity

Not every tool fits every organization. Some platforms are clearly designed for large enterprises running global transformation programs, while others are better suited for mid-sized companies or specialized departments.

Functional Scope

• Process discovery and conformance checking
• Root-cause analysis and KPI reporting
• Simulation and what-if analysis
• Task mining
• Object-centric process mining (OCPM)
• Automation and execution capabilities

What matters most is not the number of features, but their relevance to the organization’s specific use cases.

Technical Criteria

• Integration with existing system and data landscapes
• Availability of connectors and APIs
• Deployment options (cloud, on-premises, hybrid)
• Performance with large data volumes
• Data security, governance, and compliance

Integration with modern data platforms is becoming increasingly important.

Budget and Licensing Model

Pricing varies significantly across the market. Beyond license fees, organizations should consider implementation effort, operating costs, and long-term total cost of ownership (TCO).

User Experience and Adoption

Even the most powerful tool delivers value only if it is actually used. Intuitive interfaces, short learning curves, and strong service and support structures are essential for sustainable success.

Overview of the Leading Process Mining Vendors

The following section classifies relevant vendors listed in the Gartner Magic Quadrant™ for Process Mining Platforms.

Click on a vendor to jump directly to the corresponding section:

Celonis

Celonis is widely regarded as the market leader in process mining, offering a comprehensive process intelligence platform with a strong focus on execution.

Company size: Large enterprises and global corporations

• Very broad feature set
• Process discovery, conformance checking, root-cause analysis, and simulation
• Task mining via add-on modules
• Limited, proprietary OCPM
• Strong automation and execution capabilities

• Proprietary platform with separate data storage
• Extensive set of standard connectors
• High performance
• Integration with data platforms possible, but not native

Budget: Large; high total cost of ownership

• Powerful but complex
• Steep learning curve
• Strongly analyst-driven

• Large-scale transformation programs with a strong execution focus
• When budget and resources are not limiting factors

• Organizations with lean IT and data architectures
• When process mining should run directly on existing data platforms

UiPath

UiPath positions process mining as an enabler for automation and RPA within its own platform ecosystem.

Company size: Mid-sized to large organizations

• Process discovery, conformance checking, and root-cause analysis
• Very strong task mining
• Deep automation and RPA integration
• No simulation
• No OCPM

• Cloud-first architecture
• Optimized for automation pipelines
• Less suitable for strategic, end-to-end process mining

Budget: Medium to large

• Modern user interfaces
• Well suited for automation and operations teams

• When process mining is primarily used to identify automation potential
• Existing UiPath RPA customers

• Strategic, object-centric process analysis
• Scenarios where automation is not the primary focus

SAP Signavio

SAP Signavio combines process mining with process management and transformation, and is widely adopted in SAP-centric organizations.

Company size: Large enterprises with a strong SAP focus

• Process discovery and benchmarking
• Conformance checking mainly for SAP processes
• No task mining
• No OCPM
• Automation indirectly via SAP Build

• Deep SAP integration
• Limited suitability outside SAP landscapes
• High security and compliance standards

Budget: Large

• Very strong for management and transformation initiatives
• Limited analytical depth

• SAP transformation and S/4HANA programs
• When strategic process visibility matters more than operational detail

• Heterogeneous IT environments
• OCPM or data-platform-native process intelligence

mpmX

mpmX follows an open platform approach and focuses on object-centric process intelligence (OCPM). It integrates natively into existing infrastructures - such as enterprise data platforms - enabling highly performant and cost-efficient data processing.

Company size: Mid-sized to large enterprises

• Process discovery and conformance checking
• AI-supported root-cause analysis and KPI analytics
• Object-centric process mining (OCPM) as a core capability
• No task mining
• Automation options and integration with existing tools

• Native platform approach (integration with Snowflake, Databricks, Qlik, Power BI, etc.)
• Can also be used as a standalone solution
• Flexible deployment (cloud, hybrid, or on-premises)
• No data replication or proprietary data silos
• Native use of existing data models
• Very high performance on large data volumes
• Enterprise-grade security via the underlying data platform

• Medium
• Fair licensing model with unlimited scalability (new use cases do not increase cost)
• Lower TCO than traditional enterprise tools

• Self-service analytics with insights accessible to all users
• Well suited for both business departments and data teams

• Organizations with modern data platforms and complex end-to-end processes
• When OCPM, scalability, and cost control are critical

• When a fully integrated RPA or workflow ecosystem is required (possible via partners)
• Pure task-mining use cases

ABBYY Timeline

ABBYY is known for its strong combination of process mining and task mining and is frequently used to optimize operational back-office and shared services processes.

Company size: Mid-sized to large enterprises, especially shared services, back office, and operations

Functional scope:

• Process discovery and conformance checking
• Root-cause and KPI analysis
• Very strong task mining
• Limited simulation
• No OCPM
• Strong automation integration (RPA, IDP)

• Cloud and on-premises deployment
• Good standard connectors
• Strong focus on desktop and user interaction data
• Enterprise-grade security and governance

Budget: Medium; modular licensing

• Very intuitive interfaces
• High adoption in business teams
• Use-case-oriented presentation

• Operational processes with high manual effort
• Task mining as a core requirement

• Strategic end-to-end process mining across multiple systems
• Object-centric process analysis

Appian

Appian combines process mining with low-code, workflow, and case management, positioning process mining as part of a broader automation platform.

Company size: Mid-sized to large enterprises with a low-code and case management focus

• Process discovery and KPI analysis
• Limited conformance checking
• No simulation
• No task mining
• No OCPM
• Very strong automation and workflow capabilities

• Tightly integrated into the Appian platform
• Limited openness to external data platforms
• Cloud-first architecture

Budget: Medium to large; platform-based licensing

• Very good for business users
• Limited depth for process analysts

• When process mining is tightly coupled with workflow and case management
• Organizations with a clear low-code strategy

• Deep, data-driven process analysis
• Platform-independent process mining

Apromore

Apromore is an analytically driven vendor with strong capabilities in object-centric process mining, often used in complex, non-linear process environments.

Company size: Small to large enterprises

• Process discovery, conformance checking, and root-cause analysis
• Process-level simulation
• Very strong OCPM
• Limited task mining
• Automation not a core focus

• Cloud and on-premises deployment
• Highly flexible data modeling
• Well suited for complex object-centric processes

Budget: Small to medium

• Strong analytical orientation
• Excellent for experts and data scientists
• Less focused on business storytelling

• Complex end-to-end processes with multiple object types
• When analytical depth outweighs ease of use

• Business teams without process mining expertise
• Organizations expecting a strongly guided, management-oriented UI

ARIS (Software AG)

ARIS originates from the classical BPM space and combines process modeling, governance, and process mining in an integrated suite.

Company size: Large enterprises

• Process discovery and KPI analysis
• Strong conformance checking
• Model-driven simulation
• No task mining
• No OCPM
• Automation indirectly via BPM

• Strong BPM and governance framework
• Traditional enterprise architecture
• Limited focus on modern data platforms

Budget: Large

• Very good for process managers and governance teams
• Less flexibility for exploratory analysis

• Governance-, risk-, and compliance-driven organizations
• When process modeling and standards are the priority

• Real-time, data-driven process analysis
• Operational process optimization requiring deep analytics

iGrafx

iGrafx combines process mining with classical BPM, risk management, and governance, and is frequently used in regulated industries.

Company size: Mid-sized to large enterprises, often in regulated sectors

• Process discovery and KPI analysis
• Strong BPM and model-driven simulation
• Limited conformance checking
• No task mining
• No OCPM

• Governance- and model-centric approach
• Less event-log- and data-driven
• Integration into existing BPM environments

Budget: Medium to large

• Well suited for governance, risk, and compliance teams
• Less intuitive for operational analysis

• Strong focus on governance, risk, and compliance
• Organizations with a mature BPM strategy

• Exploratory, data-driven end-to-end analysis
• Object-centric process mining requirements

Pegasystems

Pegasystems tightly integrates process mining into its case management and automation platform, primarily addressing case-based processes.

Company size: Large enterprises

• Process discovery and KPI analysis
• Integrated task mining
• Very strong automation via case management
• No simulation
• No OCPM

• Deep integration into the Pega ecosystem
• Limited openness to external data platforms

Budget: Large

• Very strong for case-based processes
• High platform complexity

• Organizations with a strong case management focus
• When process mining should be embedded directly into operational workflows

• Strategic, cross-system process mining
• Open, data-platform-centric architectures

Proxverse

Proxverse is a relatively young vendor focused on lightweight process mining and research-oriented use cases.

Company size: Small to mid-sized organizations; innovation- and research-driven environments

• Process discovery and basic analytics
• Limited conformance checking
• Experimental OCPM
• No automation

• Lightweight architecture
• Limited enterprise capabilities

Budget: Small

• Simple
• Limited functionality

• Initial process mining initiatives
• Experimental or academic use cases

• Scaled enterprise scenarios
• Extensive integration or governance requirements

QPR Software

QPR is an established vendor with a classic process mining approach, focusing on stability and proven methodologies.

Company size: Mid-sized to large enterprises

Functional scope:

• Process discovery, conformance checking, and KPI analysis
• No simulation
• No task mining
• No OCPM

• Traditional process mining architecture
• Solid standard connectors

Budget: Medium

• Functional
• Less modern than market leaders

• Traditional process mining use cases
• When stability and proven methods are the priority

• Modern object-centric process analysis
• High expectations for UX and self-service analytics

ServiceNow

ServiceNow addresses process mining primarily in the context of IT, service, and support processes within the Now Platform.

Company size: Large enterprises focused on IT and service processes

• Process discovery and KPI analysis
• Strong focus on ITSM and service processes
• No simulation
• No OCPM
• Very strong automation within the Now Platform

• Deep integration into the ServiceNow ecosystem
• Limited openness to external data platforms

Budget: Large

• Very strong for existing ServiceNow users
• Limited flexibility outside the platform context

• Organizations with a strong ServiceNow footprint
• Optimization of IT and service processes

• Enterprise-wide end-to-end process mining
• Business processes beyond ITSM

Minit (Microsoft)

Minit is a classic process mining vendor focused on fast results and strong usability.

Company size: Mid-sized enterprises

• Process discovery, conformance checking, and root-cause analysis
• Limited simulation
• No task mining
• No OCPM

• Traditional architecture
• Good performance and stability

Budget: Medium

• Very strong usability
• Fast time-to-value

• Quick entry into process mining
• When usability is the top priority

• Very large or complex process landscapes
• Object-centric or data-platform-centric approaches

LanaLabs

LanaLabs provides classic process mining with a focus on transparency, conformance, and operational process analysis.

Company size: Mid-sized to large enterprises

• Process discovery, conformance checking, and root-cause analysis
• Limited simulation
• No task mining
• No OCPM

• Solid standard connectors
• Classic event-log-based approach

Budget: Medium

• Modern, clean interface
• Strong analyst experience

• Classic process mining scenarios
• When structured event logs are readily available

• Highly complex, object-spanning processes
• Architectures centered on modern data platforms

Summary: The Right Tool Depends on the Right Questions

This market overview clearly shows that there is no single “best” process mining tool. Organizations should align their selection consistently with the five core criteria - paying particular attention to architecture, scalability, and long-term economic viability.

In data-driven organizations especially, the question is increasingly whether process mining should be operated as yet another platform - or as an integral part of the existing data landscape.

Why mpmX Is a Compelling Alternative to Market Leaders

Many established market leaders offer powerful platforms - but often at the cost of high pricing, complex licensing models, and additional data silos. mpmX deliberately takes a different approach: process intelligence directly on the existing data platform, object-centric, scalable, and without lock-in.

For organizations aiming to establish process mining as a long-term, cost-efficient, and data-driven capability, mpmX represents a strategically compelling alternative to traditional enterprise solutions.