HEADQUARTERS Porto – Portugal
LATIN AMERICA OFFICE São Caetano Sul / SP – Brazil

Infinite Foundry is a 3D digital plant platform for improved production efficiency of any industrial sector.

Customers trust us

Our 3D Digital Products


3D Digital Twin of industrial facilities for remote monitoring, optimization and virtual training of workers.


3D Digital Twin of athletes for virtual training, increased performance and improved skills for competition.


3D Digital Twin of a city for urban planning, virtual tour and virtual training of emergency first responders.

3D Digital Twin

Know more about your platform


– 3D laser plant scan.
– Interior walkthrough in 3D.


– 3D real time animation of production line.


– Detect root cause of production problems.


– Plant and process simulation.


– Ergonomic motion analysis.


– Worker virtual training with VR.

A few things we’re great at

Gamification of production

Easily run production improvement scenarios.


Precise 3D model of plant enables high fidelity optimization.

No capital expenditure

Monthly subscription model.

Fast learning

Accelerated virtual training to plant workers.


Remotely monitor and solve production problems.


Receives sensor data only. Disconnected from all industrial control systems.

Industries we serve





Home Appliances


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Latest News

What distinguishes Infinite Foundry from competition?

Infinite Foundry uses 3D digital twin technology, which means it scans the facility to get a precise 3D model. From the 3D model it is possible to assist the real time[…]

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Do we do outdoor environments?

Yes, in that case we scan the outdoor environments with the laser scanner mounted on a drone or a car.

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What do we really sell? A service or a software?

Infinite Foundry sells a software that processes the data from laser scan to obtain a 3D model of the building and the and production equipment. This 3D model is animated[…]

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Contact us

Want to know how our platform can turn your plant more productive and collaborative? Get in touch with us today!

Supported by

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement Nº 878051