Example of integration between bpmn-visualization and pm4py
Generate realistic multi-agent workflow traces with LLM-enriched content, semantic validation, and PM4Py compatibility. pip install open-agent-traces
Cross-system ERP transaction forensics for SAP, Salesforce & NetSuite. Read-only anomaly detection, cross-system correlation, and evidence-grade provenance. Live no-install demo + real field case studies. MIT.
ProcessM: Real-Time Intelligent Process Mining Software
A Trie-based approach to efficiently compute alignment approximations
Process Prophet is a process minig tool that generates a process twin able to imitate existing behavior and make predictions
MCP design system validator for agentic coding. Detects design drift in agent-built UI.
Web app to generate automatic conformance checking insights using Celonis. Created as part of the “Conformance Checking in Python” software lab offered by the Chair of Process and Data Science (PADS) at RWTH Aachen University.
A modern Flet-based UI for PM4PY that enables process mining, discovery, conformance checking, filtering, and analysis of event logs without writing code.
Token-based conformance checking
Stochastic BPMN and Their Conformance
Process mining pipeline: discovery, conformance checking (as-is vs to-be), KPI/bottleneck analysis, and a Streamlit dashboard for ERP-style event logs (O2C/P2P).
Process mining on the BPI Challenge 2020 Travel Permit dataset — bottleneck analysis, conformance checking, SHAP early warning model, temporal CV
Performance Analysis of submitted International Travel Declarations from the BPIC2020 dataset
Declarative Golden Path for .NET, React, and PostgreSQL systems. A versioned architecture catalog plus deterministic, read-only conformance checks: inspect a repository, score it against a profile, and get an ordered remediation plan. Zero runtime dependencies.
Automated planning for alignment-based conformance checking - Mirror of the official SVN repository of the ProM package "PlanningBasedAlignment".
CC4Spark enables to generate XES event logs from distributed data sources, and solve conformance checking alignment problems in distributed environments.
Business Process Intelligence project focused on flood crisis management — applying process mining, automation, and simulation tools (SQL, Python, ProM, Iterop, BIMP) to analyze, model, and optimize disaster response operations for improved coordination, cost, and time efficiency.
Dataset preparation pipeline for XES event logs with fitness-guided noise injection, balancing, sampling, and train/validation/test splitting.
Process mining for LLM agent traces: where the tokens and the time actually go
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