What is AI for Systems Engineering?

AI for Systems Engineering combines industrial AI and model-based systems engineering (MBSE) to help teams develop systems architecture, simulate complex products and manage requirements traceability with AI-powered Virtual Companions. It’s especially relevant for developing software-defined, cyber-physical products in regulated industries such as aerospace and defense, transportation and mobility, and life sciences and healthcare.Industrial AI on the 3DEXPERIENCE agentic platform empowers you to tackle the obstacles that typically block MBSE adoption at scale. Continuity across systems architecture models enables you to connect tools, formats and deliverables from end to end. Our Virtual Companions help you overcome the steep MBSE learning curve by making the systems engineering process easier through natural language queries. With Virtual Companions, engineers can build, simulate and trace the virtual twin of your system while experts are kept in the loop on key design decisions.

How is AI-powered MBSE different from traditional systems engineering tools?

Compared to traditional systems engineering tools, AI for Systems Engineering adds AI-assisted guidance through Virtual Companions, helping teams create, query and refine systems models while applying established modeling practices and company standards.If you’re new to MBSE, AI for Systems Engineering is your accelerator to MBSE. Our Virtual Companions guide your team step by step through modeling methodology. MBSE proficiency comes in weeks, not years, with ROI you can see early on. Unlike AI pilots that stall at the proof-of-concept stage, this is built to scale with you from the start.If you have an established MBSE team, our Virtual Companions are configurable to your existing MBSE expertise and company guidelines, accelerating and optimizing the capabilities you’ve already built. Your specialists spend less time on repetitive modeling and more time evaluating designs. If you’ve piloted AI for MBSE and hit a scaling wall, AI for Systems Engineering helps you move past that hurdle.

Where is my data hosted and how is it secured?

Your data is hosted in the geographic region and cloud operating model selected for your service, based on your regulatory requirements, sovereignty expectations and sensitive data protection needs. Depending on the offering, this may include a public cloud, private cloud or dedicated cloud environment deployment.The Virtual Companions’ intensive computations run in dedicated AI factories. All data exchanges are encrypted and protected through continuous network monitoring, identity and access controls and threat detection.Where supported by the service architecture, data used for AI computation is processed transiently and is not retained in the AI factory after processing. These technical and architectural safeguards protect your data throughout its lifecycle. Applicable certifications and hosting conditions are specified for each service and region.

Will you train your models with my data?

No. Your engineering data remains your property. Our Virtual Companions consult your patrimony (data, design rules, history) to assist you, but it’s never used to train a shared model. If you choose to specialize a model with your data, the result lives exclusively within your own environment.

How can I trust the results Virtual Companions produce?

Dassault Systèmes’ Virtual Companions draw on dedicated skills grounded in systems engineering knowledge and know-how to guide large language models in generating trustworthy answers. Built on over 40 years of systems engineering expertise and experience deploying MBSE, our Virtual Companions produce answers based on explicit definitions of rules, skills and domain knowledge. By grounding results in explicit knowledge and know-how, the solution provides checkable outputs that humans can review and approve.

How do I get started?

Contact us through the form. An expert will evaluate your systems engineering needs and determine whether a three-month, outcome-driven pilot program is right for you. Together, you’ll explore new AI capabilities, apply them to your own data and workflows and see their impact firsthand on your existing processes. Along the way, you’ll also build reusable assets — from examples and use cases to templates and scripts — that you can continue developing beyond the pilot program.

AI for Systems Engineering and MBSE

Boost Systems Engineering Productivity With AI-Powered Virtual Companions

Watch three before-and-after demos to discover how our Virtual Companions help your systems engineering team work smarter and faster.

Quicker MBSE onboarding, adoption and diffusion

Our Virtual Companion, LEO, helps systems architects master MBSE prompting without months of specialist training. New team members can contribute within days.

Streamlined systems model simulation

LEO enables engineers to define activities, generate functions from use cases and simulate functional scenarios to identify potential issues earlier.

Smoother compliance and certification review

Skip the long stretches of manual checking and structuring. With AI, engineers can capture requirements quickly and trace them to engineering evidence.

How Industrial AI Empowers Your Team To Scale MBSE

Much of systems engineering still runs on fragmented, document-based processes. It doesn’t have to. MBSE shifts your team to a model-based approach with traceability built in from day one. Combined with industrial AI and our Virtual Companions on the 3DEXPERIENCE® agentic platform, your engineers can develop systems models faster and more consistently, even without being a Systems Modeling Language (SysML) or Modelica specialist.

Create systems architecture without the SysML learning curve

Remove the modeling bottleneck slowing down architecture decisions. LEO supports AI-assisted systems modeling in CATIA Magic, helping new team members get up to speed faster. They can generate, query and improve systems architecture without requiring advanced SysML expertise. The result? Consistent architecture shaped by your company’s rules, with your specialists freed up for the decisions that need their judgment.

Simulate systems behavior before you build

Spot a design flaw in the virtual model before it becomes an expensive physical rebuild. Ask LEO to generate an executable multiphysics model using Modelica. Then, experiment on the scenario in Dymola to see exactly how your multidisciplinary product performs under real-world conditions.

Stay certification-ready as regulations evolve

Keep certifications on track even as regulations change. AURA, our Virtual Companion, turns engineering documents into structured requirements linked to their original sources within the virtual twin, enabling requirements traceability and supporting traceability analysis for compliance. When a regulation evolves, AURA helps analyze the impact to see what’s affected — without letting your timeline slip.

Connect with our experts to set up your outcome-driven pilot

Ready to put a focused, outcome-driven pilot to work for your teams? Work with our experts to co-engineer a solution that delivers value where it matters most. Explore how, in less than three months, you can apply industrial AI to systems engineering processes, measure its impact and turn proven results into lasting capabilities — your processes, your results.

Contact us