7 Process Mining Tools Compared: Capabilities, Costs, and Where to Start

A dashboard tells you an order was late. It may not tell you that the order went through review three times before it shipped. Process mining puts those recorded steps in sequence so you can see the routes work takes, where steps repeat, and how long each order, ticket, or claim (called a case) takes.

This guide compares seven process mining tools, explains their costs and limits, and shows how to evaluate them with your own data.

Tools at a glance

Compare where you would use each tool, whether process data stays local or uses the cloud, and what you can try for free. The sections below explain capabilities, prices, and access requirements.

Seven tools and where they fit

Threadseer

Where it fitsStart inside Power BI

Threadseer runs inside a Power BI report. Map Case ID, Activity, and Timestamp, then choose Analyze this selection. You can inspect process maps and compare the different activity sequences cases follow, called variants. You can also investigate elapsed time and repeated steps, and open the cases behind a finding.

Community includes the same analytical features and calculations as Professional, within 25,000 event rows per analysis. Professional raises the supported baseline to 100,000 rows. Larger complete datasets, up to 1,000,000 rows, may be attempted when resources permit; that upper limit is conditional. If the full selection cannot load, Threadseer stops rather than presenting partial results as complete. Analysis stays inside Power BI, with no separate process mining service or platform required.

Microsoft Power Automate Process Mining

Where it fitsBuild on Power Automate

If your team uses Power Automate, ask your Microsoft administrator whether you already have Premium licenses. Premium includes process and task mining with limited stored-data capacity. The Process Mining desktop app can compare process views, including an observed process against a reference process diagram in BPMN format.

Premium and the Process Mining capacity add-on are separate purchases. The pricing table below shows both; check the included storage before deciding whether you need the add-on. Include data preparation, refresh, and any required Power BI licenses in your evaluation.

Fluxicon Disco

Where it fitsExplore exported event logs

Disco is a desktop application for exploring event logs. It imports formats including CSV, Excel, and XES, then provides process maps, variants, filters, statistics, and case histories. It is a useful candidate when you have an export and want to investigate it directly.

Try the workflow from import to a finding you can share. The demo accepts up to 100 events per file and excludes commercial use; Fluxicon offers larger, time-limited evaluations on request. For recurring reporting, work out how you will handle extraction, refresh, and distribution.

PM4Py

Where it fitsBuild custom analysis in Python

PM4Py is a Python library for discovering processes, checking observed behavior against a model, and analyzing performance. It also supports object-centric methods, which follow related objects such as orders, deliveries, and invoices together. Consider it when you need custom analysis or want to build process mining into an application.

You also own the surrounding data pipeline, interface, deployment, and maintenance. The public library is licensed under AGPL-3.0; its maintainers offer separate licensing for closed-source use. Check the terms against your intended application before committing to the implementation.

Celonis

Where it fitsMonitor connected operations

Celonis combines process exploration with operational applications and monitoring. Its Process Adherence Manager compares mined processes with modeled processes. Consider it when several teams need a maintained view of work across connected systems.

For this kind of ongoing monitoring, establish who will maintain the connections, agree on the metrics, and act on exceptions. Ask for a demonstration covering that whole cycle. Celonis advertises a free starting plan; paid pricing depends on requirements and scale.

SAP Signavio Process Intelligence

Where it fitsSupport process transformation

SAP Signavio connects mining with a broader suite for process design and transformation. Process Intelligence can check recorded work against business rules, packaged as reusable Process Atoms, and trigger notifications, workflows, or bots through integrations.

Consider it when findings need to feed a wider process-change program. Request a quote for the components you will use, and confirm that the advertised suite trial includes Process Intelligence. It can analyze work beyond SAP systems.

UiPath Process Mining

Where it fitsTurn findings into automation

UiPath brings Process Mining and Task Mining together under Process Intelligence and connects the findings with its automation platform. That makes it relevant when the people investigating a process also own the automation backlog.

Ask the vendor to follow a finding through to an automation decision. Check data import, desktop recording, analyst access, and automation execution separately. Under Unified Pricing, Process Mining uses Platform Units to license data capacity; the complete cost depends on your plan and usage. A Process Mining service trial is available for eligible Enterprise Flex plans; confirm evaluation access for your licensing model.

What getting started costs

Free access can mean a usable feature tier, a restricted demo, or an open-source library you build around. Paid plans also use different units, including users and stored-data capacity. Compare what each offer covers for your team.

Prices reviewed September 29, 2026. Dollar amounts are US prices; confirm taxes, regional availability, and billing terms. Monthly equivalents billed yearly differ from month-to-month prices. Threadseer Professional is offered through Microsoft Marketplace in the United States, and each person creating or viewing analyses above Community capacity needs an assigned license. Both Threadseer tiers require a supported Power BI environment and permission to use custom visuals.

What happens when your analysis grows?

Ask for two cost scenarios: the investigation you want to run now, and the same workflow with more data and more viewers. Specify event rows, stored gigabytes, refresh frequency, creators, and viewers. A row limit cannot be compared directly with a storage allowance.

What to check in a demo

First decide which part of the work you need to see. Process mining follows an order through recorded business events. Task mining examines the desktop actions someone takes to carry out a step, such as reviewing that order. The two approaches answer different questions and can be used together.

Process mining

Business-system records: case, activity, time

1. Order received
2. Order reviewed
3. Order shipped

Shows

The routes orders take, repeated steps, and elapsed time.

Ask

Which orders return to review? Where do their timelines differ?

Cannot show by itself

The unrecorded actions someone took while reviewing an order.

Task mining

A recorder captures desktop actions

1. Open the order
2. Check another application
3. Enter the review result

Shows

How people perform the review across applications.

Ask

Which actions repeat? Where is information copied or re-entered?

Needs separate consideration

Recorder deployment, employee privacy, and sensitive screen content.

Illustrative workflow. The highlighted review step is the task explored under Task mining. Neither view establishes the cause of a delay by itself.

Take this checklist into the evaluation

Use the same dataset and questions for each vendor. Include the people who will prepare the data and use the results. Put the report on a meeting screen and ask a business user to explain the common route and an exception without coaching. That tests readability more directly than a polished vendor demo.

Record the answers below, including any limits or extra costs. Some questions apply only to tools with desktop recording, scheduled monitoring, or automation.

Where to start

Choose one recurring question with the person responsible for the process: why some orders miss their target, which tickets reopen, or where claims return for another review. Pick a manageable group of complete cases. Scope the pilot by the data and question: even a department in a large organization can begin with a contained investigation.

Get to a first view

Prepare an event log: one row per recorded step, with a case identifier, an activity, and a timestamp. The case identifier links the steps belonging to the same order, ticket, or claim.

If milestones sit in separate date columns, reshape them into event rows first. Load the event log into your chosen tool and map the case identifier, activity, and timestamp fields. Select cases with their full histories rather than cutting off steps at a date boundary.

With prepared data and access to the tool, a useful pilot target is a first map in your initial working session. Setup time will depend on access and data preparation; record those separately from analysis time so you can see where the effort goes.

1. 01Data quality

   Check row counts, exclusions, and incomplete histories.

2. 02Main route

   Does the common path match how the team describes the work?

3. 03Exceptions

   Find loops, repeated reviews, and unusual routes.

4. 04Time

   Locate longer durations and check what each measure means.

5. 05Cases

   Open a few examples and confirm the story with the team.

Start with an exception that happens often enough to matter. Compare it with the common route, inspect individual cases, and ask the people doing the work what the records leave out. A longer route may reflect necessary checks or harder cases. Likewise, time between recorded events may include work the log does not capture; it does not prove that a case was sitting idle.

Choose your next step

Choose a tool that meets your data requirements and budget, and that your team can use to explain findings and trace them to individual cases. Test that fit with a small investigation before committing.

Bring a finding to the people who own and perform the process. Use it to start a conversation:

• Which outcome matters: turnaround, fewer repeat reviews, service quality, or something else?
• Which routes or exceptions deserve a closer look, and how many cases do they affect?
• What do the people handling those cases know that the event history cannot tell us?
• What additional fields or records would help test the explanation?
• What small change could the team try, who will own it, and how will we check the outcome?

Bring the findings to the people doing the work. Agree on one change to test and a measure of success, then return to the data to see whether the outcome improved.