Business Process Modeling

Event logs and BPMN diagrams visualize and automate business workflows for compliance and efficiency

Business impact

• Process compliance — Ensures processes adhere to rules by monitoring deviations and enforcing standards
• Process efficiency — Identifies bottlenecks and streamlines workflows to reduce cycle times and costs
• Process transformation adoption — Facilitates acceptance and implementation of new or improved business processes

Data requirements

• Event logs from enterprise systems (Structured) — Provide real-time and historical process execution data for mining and modeling
• Process documentation and interviews (Text) — Supply qualitative context and details to enrich process models
• User interaction data (Numeric) — Capture task completion and workflow adherence for performance analysis

AI methods and techniques

• Predictive AI — Forecasts process bottlenecks and compliance risks based on historical data patterns
• Generative AI — Assists in creating and editing process models from natural language descriptions
• Agentic AI — Coordinates autonomous agents to execute and monitor complex process workflows

AI models and model families

GPT-4o, Claude, Llama

Industries

Real-world evidence

1 documented case study on record.

Companies using this: KARL STORZ SE & Co KG.