modeFRONTIER, VOLTA & nDAI – Simulation, Automation and AI/ML Platforms for Life Sciences

ESTECO develops three complementary software platforms that bring simulation-driven design, process automation and artificial intelligence into engineering and R&D workflows: modeFRONTIER, VOLTA and nDAI.

modeFRONTIER is a multi-objective optimization platform that couples with any CAD/CAE/CFD/FEA tool to automatically explore design alternatives, identify optimal trade-offs (e.g. performance vs. cost vs. manufacturability) and support robust, data-driven decision making. In life sciences, possible application areas include medical device design (e.g. drug delivery systems, implants, wearables), biomechanical simulation, formulation and process optimization, and packaging design — these are just a few illustrative examples, not an exhaustive list: modeFRONTIER is a general-purpose optimization platform applicable to virtually any simulation-based design or process problem.

VOLTA is ESTECO's web platform for multidisciplinary business process optimization and the management of enterprise simulation data. It gives distributed teams a shared, version-controlled place to store, run and analyse simulation data: it executes simulations at scale via distributed execution engines, lets domain experts explore and compare results side-by-side with VOLTA Advisor, and provides Business Process Management tools (BPMN Modeler, Process Manager) to map, run and optimize an organisation's business processes.

nDAI is ESTECO's platform for building data-driven AI/machine learning models for fast, reliable predictions. It covers the full modelling lifecycle: data preparation, model configuration, training, quality validation and export for use in production. As with modeFRONTIER, the life sciences use cases mentioned below (formulation/process behaviour prediction, biomedical device performance, quality/defect prediction, process monitoring) are illustrative examples only, not an exhaustive list — nDAI is a general-purpose tool for any data-driven prediction problem.

Together, the three platforms allow life sciences companies to reduce time-to-market, improve product quality and safety, and make simulation and AI accessible beyond specialist teams.