Shared workspace of models and logs
Our collaborative repository workspace allows you to easily share process models and event logs across your enterprise.
Discovery of process maps and BPMN models
Automatically discover a process map or your “as-is” BPMN model from an event log – and dynamically switch between the two views. You can change process perspective to focus on resources, roles, business object states – and create a simplified view of your model.
Conduct powerful analyses of frequencies and durations of activities and handovers, using a range of statistic measures overlaid on a process map or BPMN model.
Focus on what matters. Reduce the complexity of your data by slicing and dicing event logs. A wide range of filtering capabilities are at your fingertips via an intuitive point-and-click interface. No coding needed. Filter by case variant, timeframe, various performance measures, specific execution paths, degree of rework, any attribute-value pair, and more.
Get the full picture with performance dashboards. See detailed statistics at different levels of abstraction using a wide range of dashboard charts. Inspect your process data case by case or by case variant, to find out who did what, when, and how often. Build custom dashboards to focus on what matters to you.
Flow comparison and multi-log animation
Visually compare two or more process variants to identify structural differences. Animate variants simultaneously to understand differences in temporal dynamics.
Rule-based and model-based conformance
Compare “expected processes”, in the forms of business rules or BPMN models, against “actual processes” as recorded in your event logs. This helps you spot discrepancies, identify sources of non-compliance and assess their impact.
Complete authoring environment
You have full control to create and edit BPMN process models, share your models, check their similarity, merge them, and use them as input for process mining.
What-if process mining
Define as-is & what-if simulation scenarios on top of BPMN models, simulate them to assess the impact of potential changes in contextual factors and interventions using a range of comparative analytics.
Connectivity and ETL pipelines
Connect with a variety of client systems and schedule custom extract-transform-load (ETL) pipelines to ingest data into Apromore at the desired cadence (e.g. weekly, monthly). Export the generated analytics for consumption via third-party BI tools.
Predictive process monitoring
Train machine learning models to predict different process characteristics and watch predictions refresh in real time, as your process cases unfold. Train your models for a variety of prediction problems, including case outcome, remaining time, next activity, and case continuation.