UK additive manufacturing service provider 3D People has deployed AMIS Runtime, a programmable build preparation engine, across its London production facility. Announced on March 3, 2026, the deployment integrates automated build preparation into the company’s polymer powder bed fusion production workflows.
The system was implemented following a 2025 grant from the UK’s Made Smarter initiative, which supported development of automated processes for preparing, nesting, and scheduling 3D print builds.
According to the companies, the collaboration combines 3D People’s experience in industrial additive manufacturing with AMIS’s programmable automation tools. The Runtime platform automates several steps in the production workflow, including file import, metadata rule handling, nesting, slicing, exporting, and continuous re-nesting of builds.
AMIS introduced the Runtime platform earlier this year as part of a broader effort to automate build preparation in industrial additive manufacturing environments. The software is designed to translate production rules into programmable workflows that automatically generate optimized build jobs for polymer and metal 3D printing systems, reducing the need for manual preparation steps and improving repeatability across production runs.
“This project marked a key step in our long-term digital manufacturing strategy,” said Sasha Bruml, Co-founder of 3D People. “It builds upon our existing MES platform, closing the loop between digital order management and physical production. The results are exciting with a more efficient, data-driven workflow that reduces human error, increases repeatability and strengthens our position as one of the UK’s leading advanced 3D printing services.”
Automating build preparation in polymer powder bed fusion
3D People produces end-use polymer components using materials including PA12 and TPU for industries such as automotive, marine, robotics, electronics, and film and television production. Customers typically require high-quality parts, short lead times, and the ability to scale from prototyping to larger production volumes.
AMIS Runtime has been integrated directly into the company’s production environment to automate the build preparation stage. Tasks such as geometry import, file repair, nesting optimization, slicing, and export preparation can now be executed through scripted workflows rather than manual setup.
“AMIS Runtime is a perfect complement to how we manufacture,” said Felix Manley, Co-founder of 3D People. “Our production relies on consistency and the ability to respond quickly when priorities change. Runtime lets us automate the repetitive tasks, so our team can focus on engineering, quality and customer support.”
Supporting factory expansion and higher build density
The deployment follows a recent expansion of the company’s London production facility, which added new SLS capacity and additional material options. According to 3D People, automating build preparation has reduced several bottlenecks previously associated with manual setup.
Using the platform, high-density builds based on AMIS’s Q*Nest nesting engine are generated automatically. The system applies consistent build rules across operators and shifts while continuously re-nesting parts as new orders enter the queue. This enables the production team to maintain updated build batches and improve overall machine utilization.
“3D People represents exactly the type of partner Runtime was built for,” said Kris Binon, Managing Director at AMIS. “Their input during development helped shape Runtime into a practical tool for their real production environment, not just a lab experiment.”
Before full deployment, the platform was validated through multiple production use cases. These included automated nesting for SLS and MJF builds, batch regeneration when urgent orders were introduced, density-aware nesting to maximize throughput, and automated metadata pipelines for traceability and documentation. According to the companies, the system has improved production efficiency while reducing manual errors in build creation.
AMIS has been expanding its software stack for industrial additive manufacturing workflows. Earlier this year, the company introduced an update to its AMIS Pro platform adding adaptive slicing capabilities for binder jetting systems, designed to improve part preparation and process control. The development reflects the company’s broader focus on automating stages of the additive manufacturing pipeline that have traditionally required manual engineering input.
Automation of additive manufacturing workflows
Efforts to automate additive manufacturing workflows are increasing as service bureaus and production facilities look to scale output without expanding engineering overhead. Manual tasks such as part orientation, nesting, and build regeneration can become significant bottlenecks when managing high-mix production environments.
Earlier this year, software developer Phasio and computational geometry firm Dyndrite introduced a fully automated workflow for HP Multi Jet Fusion production designed to generate optimized build jobs automatically. The system reduces the need for manual nesting and build planning, improving machine utilization and production consistency.
Automation is also being explored in metal additive manufacturing. At Formnext 2024, AI software developer 1000 Kelvin presented a system designed to automate large parts of the metal 3D printing production workflow, using artificial intelligence to assist with build preparation and process optimization. Developments like these highlight a broader push toward programmable manufacturing pipelines in industrial 3D printing.
3D Printing Industry is inviting speakers for its 2026 Additive Manufacturing Applications (AMA) series, covering Energy, Healthcare, Automotive and Mobility, Aerospace, Space and Defense, and Software. Each online event focuses on real production deployments, qualification, and supply chain integration. Practitioners interested in contributing can complete the call for speakers form here.
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Feature image shows AMIS Runtime interface. Image via AMIS.
