process-mining

GATs over event logs. Next-event prediction · bottleneck detection · conformance · Q-learning. PyTorch + PM4Py + Rust (588× on per-case loops).

An AI-powered process mining suite that converts natural language to process models and uses autonomous agents to analyze event logs and generate actionable process insights.

CLI tool for automated discovery of BPS models from event logs

A Python package for declarative Process Mining with Machine Learning applications

Plugboard is an event driven modelling and orchestration framework in Python for simulating and driving complex processes with many interconnected stateful components.

Python Implementation of Decay Replay Mining (DREAM)

A process mining library built upon scikit-learn!

A process mining tool written in Python3

https://arxiv.org/abs/2009.01561

Process mining module for Python.

A Python package for process-mining with DECLARE models.

Generate realistic multi-agent workflow traces with LLM-enriched content, semantic validation, and PM4Py compatibility. pip install open-agent-traces

Stack't is a small MDS-in-a box, that specializes in providing interoperability for object-centric event logs by mapping to a flexible & robust data hub.

Repository for Fuzzy Miner Web application.

PROVED (PRocess mining OVer uncErtain Data) is a library of functionalities to perform process mining on uncertain event data.

Amun is a framework that achieves privacy-preserving process mining using differential privacy.

This repository generates process mining event log features. Most of the features have been extracted from several process mining scientific papers. Please feel free to use these features in your process mining projects and contribute to the project, if you develop new ideas :)

A Deep Learning model for business process predictions. Preprint on arXiv: https://arxiv.org/abs/2102.07838

DeepSimulator is a hybrid tool between DDS and DL techniques to simulate business processes

A CLI tool for extracting event logs out of MIMIC Databases.