Are you interested? Please visit ** to see the results of our efforts.
Leveraging DeepSeek's powerful natural language processing, logical reasoning, and knowledge graph capabilities, we aim to build an intelligent ARIS process modeling platform. This solution can transform users' natural language descriptions of business processes into comprehensive, multi-dimensional ARIS process models, including process flowcharts, organizational structure diagrams, information carrier diagrams, and more. Through intelligent semantic analysis and logical reasoning, the system automatically identifies and references existing management elements (such as organizational units, information systems, data objects, etc.) while supporting the creation of new elements. This achieves intelligent, automated, and visualized process modeling, significantly improving modeling efficiency and accuracy while lowering the entry barrier for modeling.
Implementation Principles:
- Natural Language Business Process Input:
Users describe business processes using natural language, without needing to master complex ARIS modeling syntax. - DeepSeek Intelligent Semantic Analysis and Logical Reasoning:
- DeepSeek utilizes its robust language model to perform in-depth semantic understanding of the input natural language, identifying key elements such as activities, events, participants, and information carriers within the business process.
- Through logical reasoning, it analyzes the sequence, branches, loops, and other logical relationships in the business process, constructing the logical framework of the process.
- Combined with a knowledge graph, it automatically identifies and matches existing management elements while creating new elements as needed.
- Automatic Generation of Comprehensive ARIS Process Models:
- Based on DeepSeek's analysis results, the software plugin automatically generates ARIS-compliant models, including process flowcharts, organizational structure diagrams, and information carrier diagrams.
- During the model generation process, management elements are automatically linked to ensure model consistency and completeness.
- After generation, users can edit and adjust the models to meet personalized requirements.
demo:
