Autodesk NavPack is an advanced, AI-powered platform designed to bring real-time engineering insights directly into the early stages of creative design workflows.

Developed out of Autodesk's acquisition of Navasto, the platform relies on Physics AI—specifically Graph Neural Networks (GNNs)—to train on a company’s legacy high-fidelity CFD (Computational Fluid Dynamics) and FEA (Finite Element Analysis) simulation data. It then predicts structural, thermal, and fluid-dynamic performance in seconds rather than hours, allowing automotive, aerospace, and industrial design teams to iterate rapidly before running full validation passes.

The ecosystem is split into two primary licensing tiers: NavPack Core and NavPack Design.

Key Features of NavPack Core

While NavPack Design serves as the frontend client plug-in (connecting directly to tools like Autodesk Alias, Blender, VRED, or custom design dashboards), NavPack Core acts as the central engine, data processor, and licensing anchor for the platform.

1. Physics AI & Machine Learning Engine

• Graph Neural Network (GNN) Training: Houses the core machine learning infrastructure used to build predictive AI models. It ingests an organization's existing, verified simulation datasets to map out fluid and structural patterns unique to their design philosophy.

• Near Real-Time Performance Predictions: Rather than waiting hours or days for a cluster to calculate traditional Navier-Stokes equations for aerodynamics, the Core engine outputs design feasibility feedback almost instantly.

• Cross-Disciplinary "Left-Shifting": Empowers creative studios to push engineering checks to the absolute beginning ("the left side") of the product timeline, drastically reducing expensive downstream design changes.

2. Embedded Uncertainty Visualization

• Surface Uncertainty Mapping: To maintain engineering transparency, the engine calculates and generates localized visual feedback. It flags parts of a design that stray outside the boundaries of the AI's original training data, notifying designers exactly when a fallback to traditional, rigorous CFD simulation is required.

3. Workflow Streamlining & Multi-Tool Pipeline

• Unified Analytical Hub: Standardizes data models so that a single vehicle or component geometry can feed multiple engineering evaluations simultaneously.

• API and Pipeline Integration: Connects seamlessly with open-source visualization and engineering tools such as ParaView, allowing custom dashboard creation for enterprise-level pipelines.

System Requirements for NavPack Core

Because NavPack Core is responsible for running high-order AI training loops, processing complex multi-dimensional graphs, and generating instantaneous physics predictions, it demands hardware optimized for Machine Learning (ML) and heavy parallel processing.

No Return/Refund