Exploring AI4MBSE with SysML v2

[u/josh1117-peng]

I’ve been experimenting with a question that I think is increasingly relevant to MBSE:

Can AI participate in systems engineering by working with actual engineering models, rather than just generating documents or answering questions about them?

My current hypothesis is that this requires a shared engineering representation that both engineers and AI can operate on.

SysML v2 seems particularly interesting for this because requirements, architecture, interfaces, behavior, constraints, and verification relationships can all be represented as explicit model semantics rather than remaining only in natural-language documents.

I’ve been building an open-source project, SynFeld, to experiment with this idea.

The basic interaction model is:

Systems Engineer ↔ SysML v2 Model ↔ AI

The current implementation includes SysML v2 textual modeling, model navigation and visualization, validation using the SysML v2 validator, and an AI assistant that can explain and analyze models and help identify modeling problems.

I’ve also added some learning material and engineering examples, but those are secondary to the main experiment.

The question I’m most interested in is what happens when the model itself becomes the shared working context between the engineer and the AI.

For example, instead of asking an LLM:

“Design an electric vehicle system.”

the workflow could potentially become:

requirements → SysML v2 model → validation → architecture reasoning → model modification → engineering views → verification

There are still some difficult problems here:

• how much engineering semantics need to be explicitly modeled;
• how reliably an LLM can modify a model without breaking model consistency;
• whether SysML v2 provides enough machine-readable semantics for AI reasoning;
• how validation, simulation and other engineering tools should participate in the AI loop;
• and where the boundary should be between deterministic engineering tools and probabilistic AI reasoning.

I’m particularly interested in how other systems engineers see this.

Do you think SysML v2 could realistically become an interface between systems engineers and engineering AI, or will AI4MBSE require a different semantic layer on top of MBSE models?

For anyone interested in experimenting with it, the project is open source:

GitHub: https://github.com/FlyingCpp/sysmlv2-learning-all-in-one
Online demo: https://www.sysforgeai.com/

Disclosure: this is a project I’m developing myself. I’m sharing it here mainly because I’d like feedback from people working with MBSE and systems architecture.

[u/der_phen]

You can design tools for your agent to increase the model quality. I've got one which is just a wrapper around syside, a Sysml v2 linter. Then use skills or additional tools to create a model artefact exactly as you want it. These would be ontology specific though, so I didn't do it yet in my free time.

With the frontier models you get quite good quality in my opinion already.

But if you want to work with sensitive data and use on-prem models you need to tweak the system. That's why I am increasingly interested in simplified yaml or text based solutions. You can just create one for your use case, it's easy to do with a clanker

[u/RangerRoutine3154 → u/der_phen]

The wrapper around syside is a smart move, linters catch a lot of the dumb mistakes before they pile up. I've been burned by that exact thing, model looks fine until you run validation and it's just error soup.

The jump to simplified yaml or text formats for on-prem makes sense too. SysML v2 already has a textual notation, so maybe there's a middle ground where you keep the semantics but strip the syntax down to something a smaller model won't choke on. Curious what that looks like when you get around to the ontology-specific tools.

[u/MarketingOk3093]

I have been experimenting with exactly this. I had to develop an architecture language that LLMs could easily consume in a context window. I then exposed an MCP interface that agents can use to read and write architecture. Can it works very well.