What is Argus

It's auto-magic. Argus transforms documents like manuals, procedures, and drawings into interactive representations. The software automatically identifies correlations between documents and the digital twin, then creates hyperlinks to the 3D model and links structured data to equipment.

How It Works

Argus is a collection of machine learning and deep learning algorithms used to parse images and PDFs. During the process, Argus identifies text, tables, and diagram, then extracts that information into a relational database. This database is associated to the 3D digital twin to provide users with a next-generation visualization capability.


Argus: it's more than a pirate-sounding word. This transforming solution uses machine learning and algorithms to get those old legacy documents off the deck and converted into smart digital documents with a direct connection to the digital twin.

Optical Character Recognition

A machine learning technique that identifies text from any document and converts it to searchable data within a smart PDF. 

Table Extraction

Automation that extracts tables as structured data, then tags it as an interactive link to correlative components within the digital twin.

Diagram Parsing

An algorithm that interprets schematics, drawings, annotations and legends to determine how components are interconnected.

Why You Need Argus

Digital Transformation — No more scouring filing cabinets to find one detail. Argus converts legacy documents — even ones from the 80s or with coffee stains — into a searchable digital document available instantly. 

Smarter Digital Twins — Argus automatically loads the converted structured data into Beast Core and creates a digital thread as it tags equipment and links documents to the digital twin for ease of reference. 

Continuous Integration — Argus can continuously parse an organization's knowledge base. As documents are updated, Argus can scan and extract the information, then automatically update the digital twin in near-real-time.

Join the Digital Revolution
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