nTopology

nTopology, now rebranded as nTop, is a computational design platform that represents a paradigm shift in how engineers create and optimize geometry for advanced manufacturing applications, particularly additive manufacturing. The platform replaces traditional boundary-representation (B-rep) CAD modeling with implicit modeling, a mathematical approach that enables engineers to work with geometry at a fundamentally more flexible and automated level.

Implicit modeling is the platform's foundational technology. Unlike traditional CAD where geometry is defined by explicit surfaces that can break when modified, implicit geometry is defined by mathematical fields that remain valid under any transformation. This means engineers can perform complex operations like lattice generation, topology optimization, and Boolean operations without the geometry failures that plague traditional CAD workflows. nTop claims this approach enables exploring designs 10x faster than conventional methods.

In-the-loop simulation integrates FEA (Finite Element Analysis) and CFD (Computational Fluid Dynamics) capabilities directly into the design workflow. Rather than completing a design and then running separate simulations, engineers can evaluate structural and thermal performance as they design, creating a tight feedback loop that catches performance issues early. This embedded simulation approach is particularly valuable for additive manufacturing applications where complex internal geometries like lattice structures and conformal cooling channels require performance validation that traditional design-then-simulate workflows handle inefficiently.

Design automation is another core capability, enabling engineers to codify their design logic into reusable workflows. Once a design approach is established, it can be parameterized and applied across product variants without rebuilding geometry from scratch. This automation dramatically reduces the engineering time needed for product families and design iterations.

The Physics AI feature represents nTop's integration of machine learning into the design optimization process, providing AI-accelerated physics predictions that enable real-time optimization. This capability bridges the gap between time-intensive physics simulations and the rapid iteration needs of modern product development.

nTop serves over 450 engineering teams across industries including aerospace, automotive, medical devices, and consumer electronics. Notable metrics include case studies showing 3-day OML (Outer Mold Line) builds compared to 3-week traditional CAD timelines, demonstrating the dramatic productivity improvements possible. Pricing is not publicly disclosed and is available upon request.