Subaru, Honda and Neural Concept Showcase AI-Powered Engineering Innovations at Cybernet Seminar Tokyo
We attended the Cybernet Seminar in Tokyo alongside 250 experts to explore how the automotive industry can combine computer aided engineering and artificial intelligence to streamline product development workflows and improve design decisions.
The message from the event was clear. AI in CAE is moving from experimentation to practical adoption because it helps engineering teams shorten decision loops, reduce repetitive manual work, and scale high quality engineering practices across programs.
Subaru introduced "Prediction of formability of press parts for automobiles using Neural Concept", while Honda presented "Introducing Honda's automobile development process that utilizes simulation in the upstream development process with AI based performance prediction".
Introducing Engineering Intelligence
Our CEO, Pierre Baqué and Laurent D’Alvise, Commercial Director spoke at the seminar about how Neural Concept uses Engineering Intelligence to develop more efficient, higher performance products for automotive OEMs and suppliers.
Engineering Intelligence is a layer that unifies simulation, design data, and AI so teams can make faster, smarter decisions without losing control of their workflows. It turns engineering work into a more data driven, insight led process that supports earlier trade offs and faster iteration.
In practice, this means engineering teams can evaluate more design options per cycle, get quantitative feedback earlier, and focus detailed simulation on the most promising directions. In automotive, this applies across multiple domains, including external aerodynamics, thermal management, and structural component optimization.
Demand for the industry
Automotive teams are being asked to deliver higher quality products faster, while managing complexity across disciplines and toolchains. That makes connected, scalable digital engineering workflows a priority.
It was a privilege to listen to a lecture hosted by Mr Sakatu Suke from Subaru Corporation, who shared how their team is using Neural Concept to predict the formability of automotive press parts.
He explained how rising quality expectations and shorter delivery timelines are pushing press part development to move faster while maintaining engineering confidence. By reusing prior simulation results and CAD geometry, engineers can get faster feedback during early development, iterate sooner, and reserve detailed CAE for validation and final decisions.
This shift reflects a broader trend discussed at the seminar. AI in CAE is increasingly used to improve speed, consistency, and scalability of engineering decisions, especially when organizations want to reduce manual effort and increase reuse of engineering knowledge across programs.
A special thank you to our partner Cybernet for hosting this event.
Neural Concept platform
Neural Concept provides an enterprise platform to build, deploy, and run Engineering AI copilots at scale across product development workflows.
The platform enhances existing CAD, CAE, and PLM tools with AI driven copilots that automate repetitive tasks, support simulation backed trade off analysis, and deliver faster quantitative feedback during design and development.
If you would like to find out how theNeural Concept platform can work for your company, click here to learn more or alternatively schedule a demo by clicking the link below:
https://www.neuralconcept.com/contact-us
