15 Top Process Mining Tools Compared: Pricing Model, Deployment Time and Where Each Fits in 2026

Short answer

The leading platforms in 2026 are Celonis for enterprise-scale ERP optimization, SAP Signavio for SAP-centric organizations, UiPath for RPA-led automation programs, IBM Process Mining for regulated and hybrid-cloud environments, Microsoft Power Automate for Microsoft-centric organizations and KYP.ai for work that spans disconnected systems. Nine further platforms serve narrower ecosystems and budgets. 

Which one fits your needs depends less on feature lists than on two questions: where your processes actually live, and what you will be charged for. This guide compares a total of 15 platforms on data approach, pricing model, deployment speed and fit, so you can match the tool to your landscape and your budget structure. 

Key takeaways 

• The process mining market splits into system-log miners like Celonis and activity-based platforms like KYP.ai.

• Only Microsoft and IBM publish entry-level list pricing. The other 13 platforms are quote-based in whole or in part, which lengthens evaluation. 

• Data engineering, not licensing, is the hidden cost in event-log process mining. Platforms that avoid an extraction layer reach first insight fastest. 

• KYP.ai is the only solution that combines process mining and task mining features in one platform for full work visibility, and as the process intelligence layer for agentic AI readiness.

How we compared these platforms 

This guide is published by KYP.ai. We include our own platform, apply the same criteria to it as to the other nine and say where another tool is the better choice. The assessments draw on three evidence sources: customer reviews of all vendors on Gartner Peer Insights and G2, particularly on implementation effort and pricing predictability; and analyst market research from Deloitte, EY and HFS Research. 

Five criteria carry the most weight: where the platform gets its data (25%), time to first actionable insight (25%), total cost predictability (20%), AI and automation capability (15%) and fit to your existing system landscape (15%). 

Two approaches to process mining: system logs vs activity data 

System-log mining extracts event data from enterprise systems (ERP, CRM, ticketing platforms) and reconstructs process flows from what those systems recorded. Celonis, SAP Signavio, UiPath, IBM, ARIS, ServiceNow, Pega, iGrafx, Apromore, ABBYY, QPR, Appian and Automation Anywhere all take this approach. It works well when processes execute primarily within major business systems. 

Activity-based process intelligence captures how people actually work across every application (desktop, web, legacy, SaaS) without event log extraction or connector development. KYP.ai takes this approach. It reveals system transactions and the manual effort, workarounds and cross-application workflows happening between them. 

Neither approach is universally better. They solve different problems, and the rest of this guide is organized around that divide. 

1. KYP.ai: the activity-based process intelligence platform 

Best for: full work visibility across disconnected systems, and agentic AI enablement. 

Data approach: activity capture plus system data, no event log dependency. 

Pricing model: platform subscription scoped to the operation under analysis. No per-connector or per-data-volume metering, so extending scope does not re-price the contract. Quote-based. 

Time to first insight: live in days, statistically relevant insights in 3 weeks. 

KYP.ai is an Agentic Process Intelligence Platform built on three pillars. The 360 Enterprise View captures real-time data across people, processes and technology. The Business Transformation Engine quantifies inefficiencies and calculates automation ROI. The Agentic AI Enabler generates ready-to-execute agent code with structured business context. Where the 14 platforms below start from event logs, KYP.ai captures both system transactions and the human activity between them. 

Standout capabilities:

1. Speed, which front-loads the decisions. Setup in minutes. Live in days. Statistically relevant insights in 3 weeks. Measurable returns in 90 days. Teams expecting a long discovery phase will need to act on findings sooner than legacy programs condition them to. 
2. Ground truth, not event logs. KYP.ai captures how work actually gets done at the desktop, including the emails, spreadsheets, decisions and manual steps between transactions that event logs never see. For everything humans do across applications, event logs are a proxy. 
3. Conversational access to the data. KYP AI Concierge answers questions like “which processes should we automate next?” with ROI-ranked, data-backed recommendations, without requiring technical expertise. 

Where it falls short: It is a newer entrant than Celonis, SAP or UiPath, with a smaller customer base and a smaller implementation partner ecosystem. It is not an ERP transaction miner. If the only requirement is analyzing SAP or Oracle transactions from system logs, a system-native platform covers that narrower case with more pre-built extractors. 

Choose KYP.ai when most work happens across disconnected systems rather than inside a single ERP.

Choose something else when your processes execute almost entirely inside one major ERP and deep transaction-level conformance analysis is the whole requirement. 

2. Celonis: the category-defining ERP miner 

Best for: large enterprises with complex, interconnected ERP processes. 

Data approach: ERP event logs. 

Pricing model: quote-based, with consumption and module SKUs. Costs scale with data processed and with added capabilities, and implementation is a separate line. 

Time to first insight: 8-24 weeks. 

Celonis has the largest customer base, the most extensive partner ecosystem and the deepest ERP extraction in the market. Pre-built extractors for SAP, Oracle and Microsoft Dynamics handle complex data structures, and the Celocore engine provides object-centric process mining (OCPM) for processes where orders, invoices, shipments and customers interact. 

Where it falls short. Multiple add-on SKUs and tiered feature sets make total cost of ownership difficult to predict, and pricing predictability is a recurring theme in Celonis reviews on Gartner Peer Insights and G2. The platform requires substantial training, and organizations often need dedicated specialists or partner services. OCPM adds analytical overhead that simple, linear processes do not need. 

Choose Celonis when you have a complex ERP estate and the resources for a multi-month implementation. 

Choose something else when budget predictability matters more than analytical depth. 

3. SAP Signavio: the SAP-native ERP suite 

Best for: SAP customers optimizing SAP-native processes. 

Data approach: ERP event logs. 

Pricing model: quote-based across Classic, Enterprise and Enterprise Plus editions, frequently bundled into a wider SAP agreement, which can obscure the standalone cost of process mining. 

Time to first insight: 4-12 weeks. 

Acquired by SAP in 2021, Signavio provides native Business Technology Platform integration and the deepest SAP connectivity available. Automated extraction uses SAP’s own knowledge of its data structures, SAP Process Insights offers plug-and-play analytics for common SAP processes and the industry benchmark library is extensive. 

Where it falls short. Does not include task mining features natively. Strong focus on SAP data ecosystem.

Choose Signavio when you are optimizing SAP processes, especially around an S/4HANA transition. 

Choose something else when a large share of the work happens outside SAP. 

4. UiPath: the automation pipeline 

Best for: organizations running a serious UiPath automation program. 

Data approach: system event logs plus task mining. 

Pricing model: quote-based platform licensing, typically negotiated inside a broader automation contract rather than priced standalone. 

Time to first insight: 8-20 weeks. 

UiPath entered process mining through its 2021 ProcessGold acquisition and integrates discovery with its RPA platform. It combines system-level mining, desktop task mining and communications mining, with Autopilot for natural-language process exploration and an AI trust layer keeping generated insights explainable. 

Where it falls short. No object-centric process mining as of September 2026. Reviews on Gartner Peer Insights and G2 recurrently describe enterprise-grade pricing that is hard to justify without a substantial automation program already in place. Platform depth is optimized for RPA use cases rather than general process optimization or compliance. 

Choose UiPath when you want a unified discovery-to-deployment pipeline on an existing UiPath estate. 

Choose something else when process mining is the primary goal and RPA is not. 

5. IBM Process Mining: the regulated-industry option 

Best for: regulated industries needing on-premises or hybrid deployment. 

Data approach: multi-source event logs. 

Pricing model: component-based, with infrastructure, licenses and support priced separately. IBM publishes entry list prices for SaaS and on-premises, which makes it one of only two platforms here you can budget without a sales call. Full-scope cost still requires a quote. 

Time to first insight: 8-24 weeks. 

Built on the 2021 myInvenio acquisition and delivered through Cloud Pak for Business Automation, with watsonx providing prescriptive recommendations. Full OCPM compliance is combined with prescriptive AI that quantifies the benefit of each recommended action, pre-built analytics for financial services, healthcare, telecommunications and manufacturing and simulation with confidence intervals. 

Where it falls short. Platform complexity requires significant technical expertise, and business users struggle without specialists. The component-based pricing that makes entry cost visible also makes total cost hard to model. 

Choose IBM when you need hybrid or on-premises deployment with prescriptive recommendations. 

Choose something else when you need business users self-serving without a specialist team. 

6. Microsoft Power Automate: the Microsoft-stack option 

Best for: organizations whose processes run inside Microsoft tools. 

Data approach: Power Platform logs. 

Pricing model: published list pricing, per user for the Premium tier and per process for the Process and Hosted Process tiers. The most transparent pricing in this comparison. 

Time to first insight: 2-6 weeks. 

Built on the 2022 Minit acquisition, Power Automate brings process mining to the Microsoft installed base alongside RPA and document processing in one low-code environment. It connects natively to Microsoft 365, Dynamics 365 and Azure, insights flow into Power BI, and an embedded assistant answers natural-language process questions. 

Where it falls short. Pre-built analytics are heavily weighted toward Microsoft applications, with limited out-of-box support for non-Microsoft processes. Object-centric process mining is not in the shipping feature set as of September 2026, so check the current Power Platform release plan before assuming it. Cloud-only deployment rules out strict data-residency requirements. 

Choose Power Automate when your processes run primarily within Microsoft tools and budget transparency matters. 

Choose something else when the estate is heterogeneous or data residency is a constraint. 

Nine more process mining platforms worth knowing 

7. ServiceNow Process Mining. Connects natively to ServiceNow workflows with pre-configured ITSM analytics and the fastest time to first insight here, 1-2 weeks, because the data is already in the platform. Priced as a quote-based SKU on an existing ServiceNow subscription. Value is limited outside ServiceNow deployments, and non-ITSM use cases require custom development. 

8. ARIS (Software AG). Leads in governance, risk and compliance: continuous compliance monitoring, audit trails and DMN decision logic, with SaaS and on-premises options. Quote-based pricing scaled by organization size, user count and data volume. The breadth of the ARIS suite creates a high learning curve, and most buyers use a fraction of it. 

9. Pegasystems. Pairs process mining with its workflow automation platform, and GenAI Blueprint converts discovered processes into Pega application designs automatically. Quote-based, oriented around cases and platform units. Strongest for organizations already building on Pega, particularly in financial services and government. 

10. iGrafx Process360. Combines mining with decades of modeling and simulation heritage, letting process excellence teams test changes before implementation. Quote-based subscription by module and user tier. Does not offer object-centric process mining as of September 2026, and its partner coverage is concentrated in North America and Europe. 

11. Apromore. The most credible open-source entry point: a free community edition lets you validate the approach before any commercial commitment, with an enterprise edition on a capacity-based subscription rather than data volume. Strong analytics and simulation for mid-market budgets. Buyers should check partner coverage and connector availability for their own system landscape. 

12. ABBYY Timeline. An annual business subscription with enterprise pricing on quote. Strongest where process mining meets document-heavy workflows, given ABBYY’s document intelligence heritage. 

13. QPR ProcessAnalyzer. A long-established mid-market option with modular quote-based pricing, aimed at organizations that want process mining without an enterprise platform commitment. 

14. Appian Process Mining. Mining embedded in a low-code workflow platform, priced as part of Appian platform licensing. Compelling when you intend to build the fixed process in Appian immediately after discovering it. 

15. Automation Anywhere. Process discovery and task mining bundled into the automation platform contract, quote-based. Reasonable when you already run Automation Anywhere at scale and want discovery feeding the same pipeline. 

How process mining software is typically priced 

Headline license cost is the least useful number in this category, because the vendors do not meter the same thing. Five billing bases are in use, and which one a platform uses will shape your bill more than its list price. 

Of the 15 platforms reviewed in September 2026, Microsoft and IBM publish entry-level list pricing. The rest are quote-based in whole or in part, which is itself a planning fact. If a vendor will not price without a sales cycle, the evaluation timeline is longer than the pilot suggests. 

Data volume or consumption. Celonis and several event-log platforms scale with the data processed. Costs grow as you add processes and history, which makes the second year hard to forecast from the first. 

Seats. Microsoft prices per user for its Premium tier, with separate per-process and hosted-process tiers. Predictable and cheap to start, provided your processes sit inside the Microsoft stack. 

Cases or objects. Pega and platform-native options tend to price around the workflow unit rather than the analyst seat. 

Capacity. Apromore’s enterprise edition and several mid-market tools scale with operational capacity rather than raw data, which tends to flatten the curve. 

Scope of the operation observed. KYP.ai prices to the operation under analysis rather than to connectors or data volume, so adding a process or an application to the scope does not re-open the commercial conversation. 

Two costs sit outside all of these and are routinely underestimated: 

Data engineering. For event-log platforms, extracting, transforming and preparing source data commonly runs 3-6 months and carries consulting fees that can exceed the first-year license. Activity-based capture and platform-native options (ServiceNow inside ServiceNow, Microsoft inside Microsoft) avoid most of it. 

Connector development. In estates with 50 or more applications, connector work is an ongoing program, not a one-time project. 

A platform with a higher per-user cost but no data engineering phase can deliver lower total cost of ownership than a cheaper license that needs six months of preparation before the first insight. Model both lines before comparing quotes. 

A note on the expected deployment time and total cost of ownership of process mining solutions 

Look beyond licence costs. The largest cost in traditional process mining is often data engineering: extracting, transforming and preparing data from source systems, which can take 3-6 months and significant consulting fees before the first process map appears. 

A platform with a higher per-user cost but minimal data engineering may deliver lower total cost of ownership than a cheaper licence that needs six months of consulting before the first insight. 

Security and compliance at a glance 

All major platforms carry GDPR, SOC2 and ISO 27001 credentials; the differences sit in deployment and privacy models. IBM and UiPath offer true on-premises options; Celonis, Signavio, Microsoft and Pega are cloud-only with regional hosting. KYP.ai runs its agent on-premises with cloud or on-premises processing, and differentiates on privacy architecture: on-device anonymization means sensitive data never leaves the source machine. ARIS leads in GRC-specific tooling, with compliance monitoring and audit trails beyond standard certifications. 

Three key questions to compare process mining solutions 

1. Where do your processes actually live? Primarily within major ERP systems: traditional mining works well, and the ecosystem table above points to the right vendor. Spanning multiple applications with significant manual work: only activity-based capture sees the whole picture. 

2. What outcome do you need? System-level optimization suits event-log mining. Understanding and optimizing actual work patterns, including building the baseline for agentic AI, requires visibility into human activity. For the broader category context, see our guide to what process intelligence is and the process intelligence platform comparison. 

3. How quickly must you show value? Sector examples make the trade-off concrete. In BFSI, Hollard saved 307 hours/month by optimizing a single insurance process with activity-based capture, work that ran across systems event logs could not see. In BPO, where new contracts arrive with 90-day go-live timelines and no documentation, Atento reached 35% productivity improvements across multiple processes. In GBS, SPS benchmarked 8,500 employees across 20 countries to find and replicate top-performer patterns. Our process discovery handbook covers how to scope a pilot that proves value fast. 

The bottom line on process mining solutions

The process mining market has matured, but a fundamental divide remains: platforms that analyze what systems record versus those that capture what people actually do. Traditional event-log miners excel at processes that execute within major business systems; they cannot see the emails, spreadsheets and manual steps between transactions, where most operational cost and delay actually live. Answer three questions (where your processes live, what outcome you need, how fast you must show value) and the right tool follows. If the answer to the first question is “across many systems”, book a demo to see what activity-based capture finds in your operation. 

Compare specific alternatives: Celonis alternatives | UiPath alternatives | ARIS alternatives | Task mining tools compared 

Video: See how Capgemini automated process intelligence at scale with KYP.ai

Process Mining Software FAQs