
NeuralMould: Our First Digital Engineer for Injection Moulding
Seconds vs Hours
Injection moulding teams need faster iteration loops. NeuralMould compresses solver cycles into seconds.
NeuralMould is an AI model that allows engineers to iterate in seconds based on physics feedback, rather than waiting for the full exhaustive traditional simulation cycle. NeuralMould lets engineers choose geometries, select materials, and place injection gates arbitrarily to test scenarios in real time, optimize process KPIs, and avoid frozen flow fronts.
In partnership with SIMCON
Trained on over a million transient trajectories across thousands of materials, NeuralMould matches traditional solvers on filling behaviour with a fraction of the computation time. To build NeuralMould, Emmi AI partnered with SIMCON, a global leader in injection moulding CAE.
“Working with the Emmi team has been fantastic. AI is changing how engineers iterate on designs, and Emmi AI pairs deep technical credibility with a rare ability to move fast. We loved collaborating to bring it into real engineering workflows in injection molding.”
— Dr. Bastiaan Oud, CEO, SIMCON
Watch a walkthrough
Quercus Hernandez, Senior Research Engineer and one of the team members who built NeuralMould, takes a look inside the demo and shows what “in seconds instead of hours” actually looks like.
Resources
Discover NeuralMould, our first digital engineer:
Explore NeuralMould
Latest updates
Emmi AI raises EUR 15M to bring AI to the heart of industrial engineering
Funding from 3VC, Speedinvest, Serena, and PUSH marks the largest seed round ever raised by an Austrian startup and accelerates Emmi AI’s vision for AI-enabled engineering.
Emmi AI releases AB-UPT: Scaling Neural Surrogates to 100M+ Mesh Cells
Emmi AI presents AB-UPT, a novel architecture that scales neural surrogates for computational fluid dynamics (CFD) to industrial-scale problems with over 100 million mesh cells - achieving state of the art accuracy, mesh free inference, and physics consistent predictions.
NeuralDEM, Now Open Source: Real-Time Deep Learning for Industrial Particulate Flows
NeuralDEM introduced in November 2024 as the first end to end deep learning alternative to CFD–DEM multiphysics simulations, is now open source. The dataset and model enable real-time, physically consistent simulation of industrial particulate flows at production scale.
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