Explore more design alternatives earlier.
Engineering AI.
Built for Enterprise Scale.
Accelerate product development with Engineering AI powered by Neural Concept and Microsoft Azure.
Neural Concept brings AI directly into engineering workflows, connecting design, simulation, and validation. Microsoft Azure provides the cloud infrastructure, security, compute, and enterprise AI foundation required to deploy these capabilities across global engineering organizations.
Engineering teams are under pressure to develop better products in less time.
Yet critical engineering processes remain fragmented across CAD, CAE, simulation, testing, and enterprise systems. High-fidelity simulation takes time. Engineering knowledge often remains trapped within individual tools, teams, and experts.
Neural Concept and Microsoft help engineering organizations turn existing engineering data into an AI-powered product development capability.
Neural Concept integrates AI into existing engineering environments and workflows.
Together with Microsoft Azure, organizations gain an enterprise foundation for deploying Engineering AI across teams, programs, and product development processes.
- Faster design exploration
- Reduced simulation and analysis time
- Earlier identification of design issues
- AI-assisted engineering decisions
- Greater reuse of engineering knowledge
- Scalable deployment across engineering teams
39 terabytes of CFD data into a production-ready workflow in one week.
On MIT’s DrivAerNet++ aerodynamics benchmark — 8,000 vehicle geometries, public and fully reproducible — Neural Concept reached state-of-the-art accuracy running on Azure HPC infrastructure. Microsoft published the collaboration on its own Azure HPC blog.
- 39 TBIndustrial CFD dataset
- 1 weekFrom raw data to production-ready workflow
- 0.978 R²Drag coefficient accuracy on the benchmark
How it works
Connect existing engineering data from CAD, CAE, simulation, testing, and product development workflows.
Neural Concept trains AI models on engineering data, geometry, physics, and previous simulation results.
Engineers evaluate design performance rapidly without running a complete high-fidelity simulation for every design iteration.
Engineering teams explore larger design spaces and identify promising designs earlier.
Microsoft Azure provides the cloud and compute foundation for deploying Engineering AI across enterprise engineering environments.
Engineering AI across the product development lifecycle.
Use AI surrogate models to accelerate simulation workflows.
Evaluate larger design spaces and identify better-performing configurations.
Bring AI-driven predictions into engineering validation workflows.
Capture and reuse engineering intelligence across teams and programs.
Scale Engineering AI using Microsoft Azure infrastructure and enterprise services.
Neural Concept supports engineering organizations across:
See how Neural Concept and Microsoft help engineering organizations move from individual AI experiments toward scalable Engineering AI.
- Request an Engineering AI demonstration
- Discuss your engineering use case
- Explore an Azure-based deployment
- Speak with Neural Concept and Microsoft specialists
Tell us about your engineering programme.
A Neural Concept specialist reviews your request and connects you with the right engineering or partner team. Where an Azure deployment is relevant, the Microsoft team joins the conversation.
What happens next?
A Neural Concept specialist will review your request and connect you with the appropriate engineering or partner team.
For relevant Microsoft opportunities, the teams will work together to explore the appropriate Azure architecture and deployment approach.
Bring AI into the engineering process.
Move from engineering data to faster design decisions, accelerated simulation, and scalable Engineering AI.
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