9 Best Task Mining Tools in 2026: Compared on Coverage, Privacy and Pricing 

Short answer

The best task mining tools in 2026 are KYP.ai, Celonis Task Mining, Automation Anywhere, Microsoft Power Automate, IBM Process Mining, UiPath Task Mining, EdgeVerve AssistEdge, Soroco Scout and Pega Workforce Intelligence.  

KYP.ai is the best task mining tool for enterprises that need every automation opportunity ranked by ROI and turned into agent code, because it runs task mining and process mining in one platform. UiPath suits RPA teams already building in Studio, Celonis suits ERP-centric process mining programs, Microsoft suits Microsoft 365 estates on a budget and Pega suits organizations built on its case management. 

The market was worth about $2 billion in 2025 and is projected to reach $10 billion by 2033. With 24 task mining products listed on Gartner Peer Insights, the shortlist matters more than the longlist. Your choice comes down to whether you need to document tasks or to quantify and improve the processes behind them. 

Your choice depends on one question. Do you need to document tasks, or quantify and improve processes? 

Entry-level list pricing is published by Microsoft and IBM. The other eight 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 takes longer than the pilot suggests. 

What you can expect from task mining solutions in 2026 

Every task mining deployment starts with an endpoint agent, software installed on employee desktops that records user actions. Traditional tools capture screenshots plus mouse and keyboard events. Privacy-by-design tools anonymize work data on the device and send structured records in place of images. 

Analytics engines turn that capture into task sequences and time per task, then flag the points where users hesitate or rework compared with colleagues running the same process. The output usually lands in an RPA design studio or a BI dashboard for someone to analyze by hand. 

What changed in 2026 is the last step. Platforms that generate agent code automatically compress months of analysis and RPA design into days of code generation and review. 

The 9 best task mining tools in 2026, compared 

1. KYP.ai, task mining and process intelligence in one platform 

KYP.ai is a process intelligence platform with task mining at its core, and Gartner named it a Representative Vendor in the 2026 Gartner® Market Guide for Task Mining Tools, its third consecutive edition. It records keyboard, mouse, clipboard, application interactions and system calls across every desktop and web application. Capture is continuous and anonymized on the workstation, with granular configuration over exactly what is and is not recorded. 

From there, KYP.ai carries the data through three pillars: 

• 360 Enterprise View. It creates one source of truth for how people and processes interact with technology, built from continuous activity data across the whole workforce. 

• Business Transformation Engine. It quantifies inefficiency in minutes and prioritizes what to automate by dollar impact, with automation ROI calculated per department and per process. 

• Agentic AI Enabler. It generates production-ready agent code, platform agnostic by design, with error handling and escalation logic built in. Through the MCP Gateway, agents can also query process ground truth at runtime without human mediation. 

Standout capabilities 

• Speed. Setup takes minutes, the platform is live in days, statistically relevant insights arrive within three weeks and measurable returns within 90 days. 

• Ground truth from the desktop. KYP.ai sees the emails, spreadsheets, decisions and manual steps between transactions that event logs never record. 

• Conversational access. KYP AI Concierge answers questions like “which processes should we automate next?” with ROI-ranked recommendations, so business users get answers without an analyst in the loop. 

• Enterprise-scale capture. The agent is always on at less than 2% CPU, runs on Windows, macOS, Citrix and VDI, and is proven at 10,000+ concurrent workstations. 

Limitations 

• Not an ERP transaction miner. Deep SAP or Oracle transaction analysis from system logs is better served by a system-native platform with more pre-built extractors. 

• VDI needs planning. Non-persistent virtual desktops require additional configuration to keep data persistent across sessions, and KYP.ai provides guidance and tooling for it. 

Best for and pricing model 

KYP.ai: process mining and task mining in one platform for full work visibility, and the process intelligence layer for agentic AI readiness. It is the strongest fit when task mining has to produce an ROI-ranked automation pipeline and feed an agentic AI program, while teams that only need an RPA pipeline for an existing UiPath or Automation Anywhere estate will get more from those platforms. Pricing is a platform subscription scoped to the operation observed and quoted per engagement, and the KYP.ai ROI calculator estimates the return for your operation before that conversation starts. 

2. Celonis Task Mining 

Celonis built its business on process mining from system event logs and added task mining on top. Its desktop client captures user actions and fuses them with process mining, so manual steps and bottlenecks can be quantified and linked to execution actions. 

Standout capabilities 

• Linkage to process mining. Desktop task data lines up with server-level process data, from the individual click to the system transaction, and variants are prioritized by business impact. 

• Client controls and allow-listing. Administrators set capture boundaries by application and activity to meet security and privacy requirements. 

Limitations 

• Windows-centric client. The task mining client primarily supports Windows, which leaves gaps in mixed Mac or Linux estates. 

• Client upkeep. The client keeps local state and needs ongoing administration, and non-persistent VDI requires additional architecture. 

Best for and pricing model 

Celonis fits organizations that already run it for process mining and want desktop context to enrich root-cause analysis. Expect a quote built from consumption and module SKUs. 

3. Automation Anywhere (task mining) 

Automation Anywhere is one of the leading RPA platforms globally and offers task mining as a discovery capability inside its intelligent automation ecosystem. It clusters captured user actions into variants and auto-generates documentation and bot candidates, with speed to automation as the design goal. 

Standout capabilities 

• Discovery that ends in a build-ready backlog. Process Definition Documents and user stories come straight from captured activity, so candidates reach the bot team already documented. 

• One stack from discovery to run. Development and monitoring sit in the same platform, which reduces tool sprawl. 

Limitations 

• Skews toward RPA-ready work. Improvements that do not involve a bot can be overlooked. 

• Rollout effort. Desktop agents have to reach the whole user population, with clear privacy policies and consent mechanisms in place first. 

Best for and pricing model 

Automation Anywhere suits teams chasing quick RPA wins with a fast discovery-to-automation handoff inside one vendor. Its task mining comes bundled into the automation platform contract. 

4. Microsoft (Power Automate process mining) 

Microsoft built process and task mining into the Power Platform through acquisition and native development. Task capture connects to Power Automate’s low-code automation, so discovery and automation both happen inside the Microsoft ecosystem. 

Standout capabilities 

• Native Microsoft 365 integration. It connects with Teams and Dynamics 365, insights flow into Power BI, and Entra ID governance applies out of the box. 

• Low-code automation. Business users build workflows through visual interfaces without programming expertise. 

Limitations 

• Built for Microsoft estates. Capture depth falls short of specialist vendors once legacy and third-party systems dominate the stack. 

• Still maturing. Desktop capture is newer to market than at dedicated vendors, and feature depth continues to evolve. 

Best for and pricing model 

Microsoft is the pragmatic choice for a Microsoft-centric organization that wants one toolchain from discovery to low-code automation. List pricing is published per user, and the extra process mining capacity is a per-tenant add-on. 

5. IBM (Process Mining with task mining) 

IBM positions its solution for organizations that need governance and integration with its automation and AI portfolio. It combines process mining with task-level capture to deliver governed discovery of manual work and conformance analysis inside complex, regulated processes. 

Standout capabilities 

• Governance for regulated industries. Audit trails and role-based access controls are built for financial services and healthcare. 

• Portfolio integration. It connects with IBM’s RPA and workflow automation, plus watsonx AI services. 

Limitations 

• Heavier implementation. Deployment timelines run longer than lighter tools, and full value often means buying across the IBM automation stack. 

• Steeper learning curve. Technical depth makes it harder for business users to extract insight on their own. 

Best for and pricing model 

IBM fits organizations standardizing on IBM that need governed discovery in regulated processes. Its component-based pricing meters storage and user counts, with entry list prices published. 

6. UiPath (task mining) 

UiPath established itself in RPA before expanding into task mining to complete its automation lifecycle. Its task mining feeds bot development and deployment in a closed loop inside the UiPath environment. 

Standout capabilities 

• Governed discovery-to-deployment pipeline. Insights flow directly into UiPath RPA and orchestration, with approval workflows moving each opportunity forward under oversight. 

• ROI measurement. Built-in analytics compare baseline task metrics against post-automation performance. 

Limitations 

• RPA-first. UiPath is strong at what to automate and thinner on why a process runs the way it does, so improvements that need no bot get less attention. 

• Ecosystem-dependent value. Organizations without UiPath investment will find platform-agnostic options more compelling. 

Best for and pricing model 

UiPath is the natural pick for a UiPath customer that wants a governed, closed-loop pipeline from discovery to deployment. Task mining sits inside UiPath platform licensing, which is quote-based. 

7. EdgeVerve (AssistEdge Digital Observer) 

EdgeVerve, an Infosys company, brings deep experience in enterprise systems integration and legacy technology. AssistEdge captures activity across heterogeneous environments, mainframes included, with analytics to guide automation decisions. 

Standout capabilities 

• Legacy and mainframe support. It records activity on mainframe terminals and AS/400 systems that many modern tools cannot monitor. 

• Automation readiness assessment. Each process is scored on technical feasibility and business value before anyone builds a bot. 

Limitations 

• Specialist implementation. Complex legacy deployments often need specialized knowledge or Infosys consulting resources, and the interface feels older than newer entrants. 

• Few AI-driven recommendations. Capture and analysis are strong, automated insight is thinner. 

Best for and pricing model 

EdgeVerve fits heterogeneous estates where capture across mainframe and legacy systems is a prerequisite for any automation decision. Environment complexity sets the scope of each quote. 

8. Soroco (Scout) 

Soroco builds its solution around work graphs, visualizations that map how work flows between teams and systems. It suits organizations whose priority is change management and digital adoption, with automation discovery as a secondary goal. 

Standout capabilities 

• Work-graph visualization. Interactive maps reveal the handoffs and dependencies between teams that traditional process maps miss. 

• Adoption insight. Scout tracks how employees adapt to new systems over time, which informs training and change programs. 

Limitations 

• Analyst-dependent. Work graphs take training to read, and without a conversational interface extracting insight typically requires analytical expertise. 

• Lighter automation pipeline. Feeding RPA directly is less of a focus than at RPA-centric vendors. 

Best for and pricing model 

Scout fits change programs that need low-level capture and cross-team work-graph exploration. Soroco prices by quote. 

9. Pega (Workforce Intelligence and task mining) 

Pega has long held a position in BPM and case management and added task mining to show how users interact with case workflows. Existing Pega customers get a discovery-to-execution path without a new vendor relationship. 

Standout capabilities 

• Task-to-case visibility. Desktop task data connects with case flows from intake to resolution, showing how desktop activity affects SLA adherence. 

• Decisioning. Pega’s decision engine routes automation opportunities and orchestrates process changes. 

Limitations 

• Ecosystem-bound value. Organizations without Pega investment face significant cost and implementation effort to reach full capability. 

• Higher total cost of ownership. Enterprise pricing plus specialized implementation raise cost compared with lighter tools. 

Best for and pricing model 

Pega fits customers already running Pega case management who want discovery and execution on the same platform. Pega bundles task mining into its platform contract. 

Key use cases for task mining 

How to choose the best task mining tool 

1. Start from the primary use case. An RPA pipeline points to UiPath Task Mining or Automation Anywhere, which feed directly into execution. ERP process analysis points to Celonis, and continuous optimization with automatic ROI quantification points to KYP.ai. 

2. Set the privacy bar early. In regulated industries where sensitive data must never leave the workstation, KYP.ai anonymizes at source under granular configuration. Most of the other vendors offer configurable capture where policy is less constrained. 

3. Decide whether Finance needs the business case now. KYP.ai quantifies ROI automatically and Celonis supports manual modeling. If documentation is enough for the moment, UiPath and Microsoft cover it, with ROI calculation as a later project. 

4. Match the platform commitment. UiPath shops choose UiPath Task Mining, SAP-heavy estates lean to Celonis, Microsoft shops take Power Automate and Pega customers take Pega Workforce Intelligence. Vendor-agnostic buyers shortlist KYP.ai or Automation Anywhere. 

5. Size it to your workforce. Under 500 employees, Power Automate is cost-effective wherever the Microsoft licensing is already in place. Between 500 and 5,000, UiPath and Automation Anywhere are proven at that scale, and above 5,000 in a regulated industry the shortlist is Celonis or KYP.ai. 

Core capabilities across the task mining software market 

Every serious platform covers four jobs: 

1. Work recording. The agent captures what users do, and some tools sample activity to reduce storage and privacy exposure. 

2. Task and process analytics. Frequency and duration are calculated per task, so a finding reads like “data entry takes 4 hours per user per week across 47 users, or 188 hours in total.” 

3. Visualization. Flow diagrams and heatmaps let non-technical stakeholders read the work. 

4. Export and integration. Findings flow into RPA platforms or business intelligence systems. 

What separates the leaders 

• Automatic ROI quantification. Most platforms hand you a spreadsheet. KYP.ai calculates labor cost and payback period, then ranks each opportunity by dollar impact. 

• Knowing what should be automated. A process can be fully automatable and still not be worth automating this quarter, and an ROI figure on every opportunity is what turns discovery into an investment case. 

• Privacy-by-design architecture. Sensitive data is anonymized at source, on the workstation, before it ever leaves the device. Regulated industries are where the privacy conversation used to end deals. 

• Agent code generation. Leading platforms produce production-ready code for the automation platform you already run, such as UiPath, SAP Joule, Power Automate, n8n, Camunda, ServiceNow or CrewAI. 

• Continuous monitoring. Real-time tracking supports ongoing optimization, while point-in-time studies go stale within a quarter. 

• Recorded customer outcomes. Allied Global built a 3.0x ROI program, three dollars returned for every dollar invested. Hollard saved 307 hours per month on a single process, and Atos identified 56% automation potential across more than 400 use cases. 

The bottom line on task mining solutions

The task mining market offers solutions optimized for different use cases, but one question decides between them: which platform will produce insight your organization can act on and fund? 

Prioritize on five criteria. Speed to value, meaning results in weeks rather than months. AI sophistication, meaning conversational analytics and automated recommendations. Agentic AI enablement, meaning production-ready agent code with structured business context. Ecosystem fit with your existing automation and analytics tools. And capture breadth across your entire application portfolio, including legacy systems. 

KYP.ai is the strongest fit where the requirement is continuous process intelligence rather than point-in-time task documentation, and where discovery has to feed an agentic AI program. Live in days, statistically relevant insights in 3 weeks, measurable returns in 90 days. 

Ready to see what task mining finds in your operation? Book a demo at kyp.ai/book-demo to see where hours are going, which processes carry the ROI, and what the transformation roadmap looks like on your own data. 
To discover where you’re losing money, identify automation opportunities, and build data-driven transformation roadmaps—typically within 2 weeks of deployment. 

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