Software Alternatives & Reviews

StereoLOGIC Process Analytics VS LANA Process Mining

Compare StereoLOGIC Process Analytics VS LANA Process Mining and see what are their differences

StereoLOGIC Process Analytics logo StereoLOGIC Process Analytics

StereoLOGIC will help you to visualize and document business processes - what your employees do, delays in operations, weak spots and help to optimise them.

LANA Process Mining logo LANA Process Mining

Lana Labs accompanies you on the first steps towards process excellence. With LANA Process Mining you optimize automatically. Intelligent. Fast. Effective.
  • StereoLOGIC Process Analytics Landing page
    Landing page //
    2023-05-23
  • LANA Process Mining Landing page
    Landing page //
    2023-08-27

Category Popularity

0-100% (relative to StereoLOGIC Process Analytics and LANA Process Mining)
Business & Commerce
52 52%
48% 48
Office & Productivity
51 51%
49% 49
Business Process Management
Tool
47 47%
53% 53

User comments

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What are some alternatives?

When comparing StereoLOGIC Process Analytics and LANA Process Mining, you can also consider the following products

Celonis - Celonis offers process mining tool for analyzing & visualizing business processes.

Minit - Minit is a software that automatically analyzes processes and provides actionable visual insights for improving revenues, savings and efficiency.

Signavio Process Intelligence - Signavio Process Intelligence takes your data and turns it into actionable insights for your organization. Learn more with a free, personalized demo!

Process Mining - What is Process Mining? | Celonis Intelligent Business Cloud | Process Mining Software | Enterprise Performance Acceleration | Meet the world's #1 Process Mining platform: Discover, enhance, and monitor business processes and achieve process excelle…

QPR ProcessAnalyzer - QPR ProcessAnalyzer extracts and reads the timestamps used to record specific events along procurement and/or supply chains.

PAFnow Process Mining - A powerful visual to analyze your business processes based on event data