5 Best Process Mining Software for 2026 I Evaluated

If you’ve ever mapped a process that looked airtight in a workshop, then watched it fall apart once it hit real ops, you’re not alone.

Process excellence leaders and ops teams tell me this all the time: the “official” workflow is clean, but the way work actually moves through your systems, people, and handoffs is a lot messier. That’s exactly why teams go looking for the best process mining software in the first place – to see what’s really happening end to end, not what the slide deck says should be happening.

The frustrating part is how quietly problems grow. Bottlenecks and rework can sit in the background until cycle times spike or KPIs start slipping, and by then, you’re firefighting instead of fixing root causes. And when IT or transformation teams roll out automation, it gets riskier. Without a clear baseline, you can automate the wrong steps or scale inefficiency faster. The best process mining software helps you surface those gaps early, so improvements and automation bets are based on data, not gut feel.

Now I’m not an operations specialist or a Six Sigma black belt, but I evaluate software for a living, and I know how much the right tooling can change the speed and confidence of your improvement work. So, I put together this list of the best process mining software after comparing leading process mining platforms side by side using G2 Data, plus my own research. 

Here’s my top 5 picks for the best process mining software for teams: UiPath Platform, Celonis, Microsoft Power Automate, Bizagi, and IBM Process Mining.

Ready to take a close look? Read on. 

*These process mining software are top-rated in their category, according to the G2 2026 Winter Grid Report. I have mentioned the starting price of their paid plans and standout features for easy comparison. 

Top process mining software ranked by G2 feature ratings

Here’s a quick comparison table showing how each process mining software stacks up on the features that matter most for day-to-day collaboration, along with their G2 feature ratings based on G2 2026 Winter Grid Report.

5 best process mining software I recommend

At a basic level, process mining tools pull event data from the systems you already run (ERP, CRM, ITSM, finance apps) and reconstruct the real path work takes, every variant, detour, and delay included. I like to think of it as going from “what we think the process is” to “what the process actually is,” with timestamps and proof.

What separates the best process mining tools from the rest is how actionable they are. The strong ones help you compare reality to your intended model (conformance), show why bottlenecks happen, and point to the fixes that will move KPIs fastest (enhancement). Even better, they connect those insights to automation readiness, so you’re deciding what to optimize or automate next with confidence.

On G2, these tools are already serving a broad mix of buyers: 29% small business, 29% mid-market, and 42% enterprise. That spread tracks with what I see in G2 reviews: smaller teams want faster visibility and quick wins, while enterprises lean on mining to standardize and scale improvement across complex, cross-system processes.

And the market momentum backs this up. The global process mining software market is projected to reach $21.92 billion by 2030, growing at a 59.4% CAGR from 2025 to 2030.

Growth numbers aside, the takeaway is simple: more teams are using process mining not as a “nice-to-have analysis,” but as a core engine for process visibility, bottleneck reduction, automation planning, and ROI reporting.

What makes the best process mining software: My selection criteria

To land on these picks, I looked at what kept surfacing in G2 Grid® Reports, satisfaction data, and review themes. I wanted to know does this tool help teams discover the real process, validate it, improve it, and confidently tie it to automation and ROI.

• Process discovery that reflects reality: I looked for tools that ingest event logs cleanly and reconstruct the true “as-is” process, including variants and exceptions, not just the happy path. The best ones make it easy to zoom from high-level flows down to case-level details with timestamps you can trust.
• Conformance and compliance clarity: I prioritized platforms that compare actual execution to the intended model and highlight deviations in a way that’s easy to act on. Extra points when conformance checks support rules, thresholds, and audit-ready reporting for regulated workflows.
• Actionable enhancement insights: I paid close attention to how well tools identify bottlenecks, rework loops, and root causes, not just where delays happen. The best software connects those insights to concrete improvement levers, like handoff reductions, queue fixes, or policy changes.
• Automation readiness and recommendation depth: I looked for clear signals on which steps are stable, repetitive, and high-impact enough to automate, along with why. Strong tools go beyond “this looks automatable” and show volume, variability, exception rate, and projected impact so teams can prioritize intelligently.
• Integrations and data coverage: I evaluated how broadly each platform connects to core systems (ERP, CRM, ITSM, BPM, data warehouses) and how flexible it is with messy, multi-source data. If getting usable logs requires heavy lift or custom workarounds, adoption usually suffers; reviews made that loud and clear.
• Usability for both ops and technical teams: I looked for tools that make sense to process excellence leaders and don’t frustrate IT/analytics teams. The best ones balance no-code exploration with deeper analytical controls, so different users can collaborate without tripping over the interface.
• ROI reporting and stakeholder storytelling:I focused on whether the tool helps teams quantify gains like cycle time, cost, throughput, compliance risk, and package them into dashboards that leaders actually use. If a platform can’t clearly show “here’s what improved and here’s what it’s worth,” it’s hard to sustain momentum.

No tool is perfect across every criterion, and you’ll see trade-offs in the picks. But the best process mining software I have on this list is consistently strong where it counts: trustworthy discovery, practical insights, automation guidance, and clean reporting that helps teams move from visibility to measurable change.

The list below contains genuine user reviews from the Process Mining software category. To be included in this category, a solution must:

• Track event logs to discover actual business processes
• Perform conformance checks to identify inconsistencies or abnormalities in business processes
• Provide organizational insights into which employees are deviating from the norm
• Integrate with existing business software and IT infrastructure

*This data was pulled from G2 in 2025. Some reviews may have been edited for clarity.  

Microsoft Power Automate is Microsoft’s workflow automation hub, and in a process mining context, I think of it as the “connective tissue” between what you uncover and what you actually fix.

It helps you map and monitor processes across the Microsoft stack (and plenty of third-party apps), then turn those insights into automated flows, approvals, and notifications without a ton of custom build. So if your team already lives in Microsoft 365, Dynamics, or Azure, Power Automate tends to feel like a natural extension of how work gets done.

For operations teams, Power Automate stands out for its governance, monitoring, and reliability features, like flow run histories, error handling, alerts, and environment control, that make it possible to scale automation without creating operational risk. It also supports controlled rollouts and quick rollback, which matters when process changes impact revenue, compliance, or customer experience.

Based on my analysis of user reviews, G2 users back that up in a pretty consistent way. Satisfaction scores are strong where adoption usually lives or dies: ease of use is rated at 91%, ease of setup at 90%. Reviewers like how quickly they can get value because connectors are ready to go, and building flows doesn’t require heavy engineering.

The highest-rated features on G2 tell the same story: integrations (89%), autonomous task execution (89%), and collaboration (88%), which makes sense for process teams that need cross-app visibility and an easy way to operationalize improvements.

According to G2 reviews, the platform is incredibly capable for cross-app automation, and teams running lots of flows appreciate that flexibility, but those wanting lightning-fast execution on very large, high-frequency automations might want to account for occasional performance lag and plan critical workflows accordingly.

And while the low-code experience is approachable for many users, teams aiming to build complex, multi-branch logic or enterprise-wide orchestration should invest in learning and enablement early, so things stay clean as usage grows, based on a few reviews I read.

Overall, I’d recommend Power Automate most for process excellence and ops teams who want process visibility that turns into fast automation wins inside a Microsoft-heavy environment. If your priority is “find it, fix it, automate it” without leaving your stack, this is a punchy, practical pick.

What I dislike about Microsoft Power Automate:

• Based on the G2 reviews, I get the sense that teams running a high volume of automations value how flexible Power Automate is, but groups wanting ultra-fast execution at scale will need to account for occasional performance lag and design critical flows with that in mind.
• I also notice that while many users start quickly with simple flows, teams aiming for complex, multi-step orchestration should expect more complexity and plan for governance and enablement so things don’t get messy as they grow.

What G2 users like about Microsoft Power Automate: 

“Debugging isn’t intuitive, and error messages are often unclear, making troubleshooting time-consuming. High-volume automations may exhibit latency or unexpected errors.”

– Microsoft Power Automate review, Luca P.

Looking to streamline workflows and improve operational efficiency? Explore the best business process management software on G2 to see which platforms teams rely on to automate and optimize their processes.

UiPath is one of the automation-first process mining leaders, meaning its big advantage is how tightly mining feeds directly into automation. What makes UiPath different, in my view, is that process mining is not a standalone island. It’s built to seamlessly integrate with RPA, AI agents, and low-code automations.

The Agentic Automation is UiPath’s way of bringing process mining and automation together in one ecosystem, so you can spot how work really flows and then act on it without jumping tools.

When I evaluated it alongside the others, what stood out right away, both in G2 data and in reviewer language, is that UiPath is built for teams who don’t just want insight, they want execution. Users consistently describe the platform as reliable, feature-rich, and genuinely useful for moving from “here’s the bottleneck” to “here’s what we automated to fix it.”

On G2, that shows up clearly in the satisfaction scores: Ease of use is rated at 97%, quality of support is 96%, and ease of setup is 91%.

And the highest-rated features line up with what process mining teams care about most once they’re past discovery: RPA integration (97%), application development (97%), and integrations (96%).

Reviewers love that UiPath doesn’t leave you stuck at diagnosis. You can mine processes, validate what’s off, and push directly into automation with strong orchestration and a mature RPA backbone. The breadth of integrations also gets real praise because it makes the picture more complete across systems, which is where process mining either shines or falls apart.

Based on G2 reviews I looked at, users who want automation depth seem to feel the pricing is justified, but teams looking for lightweight mining or smaller-scope rollouts may find they want to plan their budget and should go in with a clear ROI plan. Also, reviewers appreciate the platform’s usability once they’re up and running, but teams newer to process mining or automation will want to budget time for enablement and probably lean on UiPath’s training and support early on.

Net-net, UiPath Agentic Automation is the best fit for process excellence, IT, and transformation teams that want process mining tightly connected to automation at scale. If your goal is to turn process visibility into real, repeatable fixes, not just insights, this is the platform I’d bet on.

What I dislike about UiPath Platform™ for Agentic Automation:

• I’ve seen plenty of reviewers say the platform is powerful and worth it for automation-heavy programs, but teams that want lightweight process mining or have tighter budgets will need to plan for higher costs and make sure the ROI case is clear.
• I also notice that while users like UiPath once they’re fluent in it, teams newer to process mining or automation should expect a learning curve and budget time for training and enablement so they don’t stall early on.

What G2 users dislike about UiPath Platform™ for Agentic Automation: 

 “Since I’m still learning UiPath, some features can be overwhelming at first — especially when dealing with more advanced activities or debugging errors. The platform is powerful, but sometimes the interface feels a bit complex for beginners. I also noticed that it could use a lot of system resources, which makes it run slower on lower-end machines.”

– UiPath Platform™ for Agentic Automation review, Hosny G. 

I am sure that you’ve probably heard of Celonis before if you have been digging into process mining tools for some time. Celonis is a well-known, dedicated process mining platform built to show you how work actually flows across your systems, not how it’s supposed to flow in a diagram.

At its core, Celonis pulls event data from tools like ERP, CRM, and ticketing systems, reconstructs the real “as-is” process, and then helps you pinpoint where time, cost, or compliance drift is creeping in. From what I found during my research, Celonis reads as a process-first leader: the product starts with deep discovery and analysis, then layers on improvement guidance, monitoring, and operational follow-through.

That focus comes through in G2 Data and reviews I saw. Satisfaction is strongest around the day-to-day partnership and usability for power users. Ease of doing business sits at 91%, and reviewers routinely say the platform is dependable once it’s in place.

From my research, Celonis’ standout feature is its process intelligence graph, which builds a “digital twin” of how processes actually run across systems. I also found that its execution management layer goes beyond dashboards by recommending fixes and triggering actions when cases drift off-path. The depth of variant analysis and object-centric mining also looks built for messy, real enterprise workflows.

The highest-rated features on G2 reinforce these core strengths for process teams: process mapping (88%), real-time process analysis (88%), and execution management (87%).

Users like being able to move from a high-level process view to case-level reality quickly, and they call out how real-time monitoring makes it easier to keep improvements from slipping back over time.

And according to reviews I read, users working in complex enterprise environments consistently point to Celonis’ process visibility as a major payoff, especially when they’re managing high-volume workflows across systems. Teams looking for a lighter-weight entry point or narrower use cases will want to plan for a higher price tag.

Also, users clearly trust the depth of insights Celonis offers, but teams that are newer to process mining should expect a learning curve up front. Celonis rewards curiosity and analytical work, so setting aside time for onboarding and internal enablement pays off.

If your priority is to get a brutally clear, data-true view of your processes and keep them improving in real time, Celonis is one of the best process mining software options out there. I’d recommend it most for process excellence, ops, and transformation teams in mid-market to enterprise environments who want serious discovery and continuous execution management, not just a one-off process map.

What I dislike about Celonis:

• From the G2 reviews I read, I get the sense that teams who want deep, enterprise-level visibility across complex systems feel Celonis delivers real value, but smaller teams or those with narrower mining needs will need to plan for a higher investment to make the ROI equation work for them.
• I also noticed on a few G2 reviews that teams newer to process mining should expect a ramp-up period and budget time for training so they can fully unlock the depth Celonis offers.

What G2 users dislike about Celonis:

“The initial setup and data integration phase can be complex and time-consuming, requiring significant technical effort. Additionally, the licensing model can be challenging to navigate and optimize for smaller-scale use cases within a larger organization.”

– Celonis review, Adithya P.

Bizagi is essentially a process management and automation suite with process mining baked into the picture, and I think of it as a model-and-improve tool for teams who want both a clear view of how work runs and a practical way to design what comes next.

In plain terms, it helps you map your real processes, compare them to how they’re supposed to run, and then standardize or automate improvements inside the same environment. When I look at it through a process mining lens, Bizagi feels like a strong fit for organizations that want process discovery and governance to live alongside BPM and low-code execution, not as a separate analytics island.

G2 Data lines up with that story. Users rate Bizagi highly for the things that make process mining feel usable in the real world: Ease of Use is strong, support is well-regarded, and people say the platform meets their requirements consistently.

The highest-rated features on G2 are exactly what you’d want in a process-first too: Real-time process analysis, a process library that keeps models and learnings reusable, and process mapping that’s clear enough for both ops and IT to work from. Reviews I’ve seen tend to highlight how approachable the modeling experience feels, and how helpful it is to keep discovery, documentation, and improvement work connected instead of scattered across tools.

Because the platform can do a lot, from mining to modeling to execution, teams aiming to use the deeper capabilities should expect a bit of ramp-up time to set standards and get everyone working in the same way. And for teams scaling into larger, more complex workflows, it’s worth keeping performance in mind: users note implementation is straightforward for most processes, but bigger, high-volume workflows can sometimes feel a little slower. That’s a pretty common pattern across process mining tools, but it’s useful to account for as you grow.

My bottom line: Bizagi is a great pick for process excellence and transformation teams who want process mining plus structured process management in one place. If you’re trying to go from “show me the truth” to “let’s redesign and run it better” without tool-hopping, Bizagi is a smart, steady choice.

What I dislike about Bizagi:

• Users on G2 value that teams who want a tool that’s easy to pick up quickly feel Bizagi delivers on that, but users wanting to go deep into the more advanced features should expect a learning curve and plan time to really master the platform.
• G2 reviews observe that teams working on smaller or moderate workflows tend to have a smooth experience, but those needing to scale process mining across large, complex workflows should account for occasional lag and design rollouts with that growth in mind.

What G2 users dislike about Bizagi: 

“Although robust, Bizagi can become cumbersome in complex projects, with noticeable slowness when handling large models.”

– Bizagi review, Rafael L.

I think of IBM Process Mining as a steady, enterprise-ready platform for uncovering how work actually moves through your organization. It uses system data to reveal the real path processes take, then makes it easier to spot friction points and build a clear improvement plan around them.

At the core, it ingests event logs from your systems and generates as-is process discovery (the real flow vs the designed flow),  variant and bottleneck analysis (where time/cost/leakage happens), conformance checks against your intended model or policy, automation recommendations + ROI sizing to prioritize what to fix first. And if you’re already IBM-automation-led, the �