Digitization Companion

The Digitization Companion (DigiCo) is a cutting-edge, AI-powered tool designed to automatically digitize and analyze engineering diagrams. Our primary focus is on Piping and Instrumentation Diagrams (P&IDs), transforming them from static documents into intelligent, editable, and data-rich assets. Our mission is to eliminate the tedious and error-prone process of manual digitization, saving you time and resources.

In just a few minutes, the Digitization Companion can process a complete P&ID, reducing manual effort by up to 80%. This allows teams to focus on what they do best: engineering and innovation.

Features

  • Automated Data Extraction
    Our AI accurately identifies and extracts all relevant information from your diagrams, including symbols, text, tables, lines, and connections. This minimizes the risk of human error and ensures data integrity.

  • Seamless Integration
    The Digitization Companion is compatible with existing CAE software and supports a variety of export formats, including the DEXPI standard, CSV, JSON, and XML.

  • Secure and Confidential
    We prioritize the security of proprietary data. All files are protected with robust encryption and stringent security protocols.

  • Collaboration Tools
    Our platform facilitates teamwork by allowing multiple users to manage and work on projects simultaneously.

Technology

The Digitization Companion leverages advanced machine learning algorithms to understand and interpret complex engineering diagrams.
Our AI is trained on a vast dataset of P&IDs, enabling it to recognize a wide range of symbols and notations with high precision.

By converting engineering diagrams into a digital format, the Digitization Companion prepares engineering data for the future of process engineering.
This includes enabling AI-powered HAZOP analysis, autocorrection of diagrams, and predictive maintenance.

👉 See our current research projects for examples of use cases that leverage digitized P&IDs.

Request a Demo

We are currently preparing for the launch of our beta demo.
If you are interested in seeing the Digitization Companion in action and learning how it can benefit your organization, please contact us to schedule a demonstration.

Relevant Publications

  • Theisen, M. F., Flores, K. N., Balhorn, L. S., & Schweidtmann, A. M. (2023).
    Digitization of chemical process flow diagrams using deep convolutional neural networks.
    Digital Chemical Engineering, 6, 100072.
    https://doi.org/10.1016/j.dche.2022.100072