ProMoAI: Process Modeling with Generative AI

Humam Kourani, Alessandro Berti, Daniel Schuster, Wil M. P. van der Aalst
3/7/2024
cs.DBcs.CL

No confident code implementation found for this paper.

Abstract

ProMoAI is a novel tool that leverages Large Language Models (LLMs) to automatically generate process models from textual descriptions, incorporating advanced prompt engineering, error handling, and code generation techniques. Beyond automating the generation of complex process models, ProMoAI also supports process model optimization. Users can interact with the tool by providing feedback on the generated model, which is then used for refining the process model. ProMoAI utilizes the capabilities LLMs to offer a novel, AI-driven approach to process modeling, significantly reducing the barrier to entry for users without deep technical knowledge in process modeling.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{kourani2024promoai,
  title  = {ProMoAI: Process Modeling with Generative AI},
  author = {Humam Kourani and Alessandro Berti and Daniel Schuster and Wil M. P. van der Aalst},
  year   = {2024},
  eprint = {2403.04327},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2403.04327v2}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2403.04327.svg)](https://codeofpaper.com/paper/2403.04327)

Discussion