Complexity reduced – AIoT now as simple as an app!

The focus is on DATA and empowering DATA in industrial environments.

COLIGO – Latin for merge – is a software solution that enables the Digitalization of industrial processes by merging the Operational Technology and Information Technology worlds in a simple, effective, and user-friendly manner. COLIGO Edge AIoT Software targets edge computing devices that act as an interface – at the Data Technology (DT) Level – between industrial processes (OT) and business operations and enterprise information systems (IT).

Who is COLIGO for?

The Automation Engineers!

Automation engineers know their machines and the processes the best. This is why THEY are at the center of our solution and why we developed COLIGO so that THEY can manage and benefit from the machine and process data with a single comprehensive app.

What is COLIGO composed of?
COLIGO is a Software Solution comprised of the following key parts:

COLIGO EdgeStack

A portable, docker-based, real-time Linux environment with functionality that includes:

  • Data collection over OPC UA
  • Data Storage
  • Data monitoring (configurable dashboard)
  • No code AI models, ready-to-use
  • Exposure of selected data to ERP, MES or Cloud for further processing

The COLIGO EdgeBox host hardware is optionally available.


A progressive web app that allows users to select the data to be collected, stored, analyzed, monitored, and exposed within a few clicks – users are not required to have specific knowledge outside their machine and process expertise.

COLIGO Cockpit

The Management Suite for device and fleet management, Firmware and container updates, users management and business operations.

Use Cases


  • Collection of machine/process data
  • Secure transfer of data between OT and IT
  • Secure access to automation systems i.e. software update
  • Secure access to machine/process data
  • Remote monitoring of key machine information in a customized dashboard
  • Local treatment of data vs third party cloud systems
  • Remote maintenance and firmware updates

Including AI

  • Anomaly Detection
  • Predictive Analytics (failure, quality, energy consumption)
  • Image and Video Analytics (recognition, verification, classification, detection)
  • Noise recognition
  • Quality control (deviation from recipes, subtle abnormalities in behavior, change in raw materials, etc…)