Process mining and AI
Use Artificial Intelligence to provide visibility, analysis and better understanding of business operating models - through real-time information on current performance and indicators for potential improvements.
Process and Performance Mining in the Digital Era
As enterprises’ view of business processes evolve from static, rote sequences of tasks to a dynamic, customer-focused context, so too do the business process management (BPM) platforms that help such organizations manage and automate those processes.Download the whitepaper
Enhancing human intelligence with AI technology: better information leads to better decisions
Behind-the-scenes AI process mining algorithms analyze archived data to detect patterns, and then apply them to ongoing process executions to predict issues and inefficiencies.
Users gets real-time information on how processes are currently performing and where they can take action if needed.
Human decision-making intelligence is boosted with machine learning to avoid bottlenecks, improve efficiency, and highlight possible process improvements.
Process mining - enterprise-ready AI, a BPM innovation
Unlike classic process mining techniques that focus on process discovery, our use of an innovative process mining extension allows learning on any business process model already automated in the BPM platform.
Offers goal-oriented predictions
No need to know data in advance
Provides easy-to-interpret results
Detects outliers, loops, latencies, and bottlenecks in a live process application
Analyzes at the level of processes, paths, and tasks
Considers both actual and predicted durations and occurrences
Source: Process Mining, Data Science in Action, Wil van der Aalst, 2016
“Process mining is much more than process discovery…I see a trend toward predictive process mining. It is not enough to diagnose problems; tools should also be able to predict delays and deviations before they happen.”
Prof.dr.ir. Wil van der Aalst, Process and Data Science, RWTH Aachen University
Business Activity Monitoring
Create dashboards using historical data stored in Elasticsearch and detect outliers, loops, latencies and bottlenecks in your operating business models.
Combine BAM and process mining approaches to provide visibility, analysis and understanding to users on how they are currently performing, and find opportunities for improvement.