Neural Concept Launches MCP Bridge, Augmenting AI Agents to Operate Industrial Engineering Software

• AI agents can now operate commercial CAD and simulation software such as CATIA, NX and Abaqus, inside enterprise environments.
• Neural Concept benchmarked AI models on real engineering tasks and tuned them to each one, so every step of the design and simulation workflow runs on the best-suited model.
• MCP Bridge is already deployed by leading organizations in automotive, aerospace, electronics and energy to bring higher-performing products to market faster.
• Available now and on show at Neural Concept Connect, opening October 20 in the San Francisco Bay Area.

San Francisco, CA – October 19, 2026 – Neural Concept, the Swiss AI-native engineering company, today launched MCP Bridge, the first capability to help AI agents operate commercial CAD, meshing and simulation tools in hybrid environments and at enterprise scale. With it, AI agents carry out real engineering work inside the software used to design and simulate physical products, the way an engineer would.

AI has already transformed how software is built. Every physical product starts in engineering software, which makes it AI’s next frontier.

Large engineering organizations operate across complex software environments, licensing structures and security policies. In a typical simulation cycle, running the solver is the only step that needs no engineer. The work around it, from retrieving the right geometry and cleaning it up to meshing it, setting up the physics and feeding results back into the design, remains hands-on and often spans multiple tools. With MCP Bridge, Neural Concept gives agents both access to these tools and the engineering know-how to use them, while companies retain control and ownership of their programs and data.

“For the first time, the software that shapes every physical product can be operated by AI at enterprise scale,” said Pierre Baqué, CEO and co-founder of Neural Concept. “The real opportunity is to give engineers more leverage, so they can take on harder problems and solve them faster.”

This capability comes at a time when manufacturers face growing pressure to shorten product development cycles, while engineering experts remain a scarce resource. When agents handle approved tasks inside design and simulation software, every hour they take on is an hour handed back to performance optimization. In one customer case, an engineer using MCP Bridge cleaned up the geometry of a wheel rim in approximately three minutes, compared with a day using the manual process.

The engineering workflow for a physical product moves from design through model preparation to simulation. Neural Concept has built connectors for major commercial tools at each stage: CATIA and NX for design, ANSA and HyperMesh for model preparation, and Abaqus for simulation, with more to come based on customer demand. Built on the open Model Context Protocol, MCP Bridge lets agents carry work from CAD to mesh to solver across a company’s Windows workstations and Linux clusters, without engineers leaving Neural Concept.

Neural Concept users at TRATON and OPmobility are already putting AI agents to work in engineering. Their engineers point to the same next step: giving those agents the ability to operate the CAD and simulation tools their teams already rely on.

“AI agents have completely changed the way I work,” said Ciro Alosa, Electromagnetic Design Engineer at TRATON and Neural Concept user. “I can run more work in parallel, and going from a research paper to a validated script in our simulation toolchain now takes a couple of days. The next-generation engineer focuses on planning and evaluation, managing teams of AI agents working towards a goal. When agents can operate the engineering tools we already use, nothing is out of reach anymore.”

“At OPmobility, we are exploring how AI agents can operate the CAD and simulation tools our engineers already use,” said Yoann Eulalie, R&I Group Leader at OPmobility. “The aim is to give engineers more time to explore design options, while they keep full control of the decisions that require engineering judgment.”

MCP Bridge was designed with that aim: agents take on the hands-on steps inside the tools, while engineers set the goal and validate the results. Beyond access, the connectors carry the engineering know-how behind each tool, tailored to each team’s rules and established ways of working, so agents adapt to engineers rather than the other way around.

Because each stage of an engineering workflow requires different capabilities, the top-performing model varies by task. Neural Concept benchmarks models on real engineering tasks, including CAD editing and meshing, so companies can select the model most suited to each task as new models become available.

MCP Bridge is available now to Neural Concept’s customers and extends each company’s Engineering Intelligence Layer. Next, agents will not only operate a company’s tools but learn how it designs. MCP Bridge will be presented first at Neural Concept Connect US this week, followed by Neural Concept Connect Europe in Munich on November 24.

About Neural Concept

Neural Concept provides the intelligence layer for engineering, enabling companies to design and develop complex, high-performance products faster and more efficiently. Its AI-native platform embeds physics-aware intelligence directly into design and simulation workflows, empowering engineering teams to make continuous, AI-augmented decisions at every stage of product design.

Founded in 2019, Neural Concept serves leading OEMs and engineering organizations across automotive, aerospace, energy, consumer electronics, semiconductors and defense. Headquartered in Switzerland, the company has a growing global presence including offices in Munich, New York, Seoul and now India (Bengaluru and Pune), and is backed by global investors, including Goldman Sachs, Forestay Capital and D. E. Shaw Group. Visit www.neuralconcept.com.

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