$23+ billion

additive manufacturing market share

1.42 million

3D printers purchased in 2020


expected annual growth rate in additive manufacturing industry


3D Systems turned to TensorIoT and AWS to handle migration of their backend system to better incorporate machine learning (ML) into their processes.


Improve 3D System’s back-end system to allow for machine learning and maintain a seamless workflow and output.


3D Systems is positioned to take the next leap in their progression and start bringing ML into their existing workflows.


3D Systems is a leading additive manufacturing solutions company.
When looking at adding machine learning to their processes, 3D Systems quickly learned their existing backend system was not capable of performing machine learning (ML) functions. This meant 3D Systems needed to migrate to a backend platform that would prove capable of incorporating ML into their workflows. AWS was selected on the basis of its feature-rich ecosystem, which can easily integrate and expand the ML workflows to support 3D Systems as they continue to produce world class products.

The Challenge

3D Systems’ excellent user interface (UI) masks a very complex device communication process. Without altering the UI, what’s the best method to ingest and store the printer information in the new backend infrastructure? This process involves multiple protocols in containers, with multiple printers connected to one gateway, and the connected printers communicate at different rates and produce a variety of telemetry messages, corresponding to the printer state or job status.

The Solution

In order to find a solution that would cover both greenfield and brownfield devices, 3D Systems teamed up with TensorIoT and AWS Professional Services to migrate their backend platform to AWS. Using the feature-rich AWS ecosystem allowed for easy integration and expansion of ML workflows to support 3D Systems production. This collaboration ensured 3D Systems has the ability to incorporate ML into their enhanced workflows.