AI-Assisted Geometry Creation
AI-Assisted Geometry Creation
Geometry work has a routine layer. We turn it into functions you can run — not prompts you have to babysit.
AI-assisted geometry creation is the discipline of letting AI do defined geometry work in Siemens NX — preparing PMI from your norms and templates, editing existing geometry on instruction, and generating new parts and variants from parametric master templates — packaged as functions, workflows and reviewable jobs built on NXOpen. Every run produces reviewable results with a confirm gate before anything is committed, and everything that leaves the pipeline is parametric: real features, real sketches, real expressions.
This is deliberately not a chatbot. If your team prefers to drive the same discipline conversationally, that entry point exists — our NX AI Assistants & Chatbots family, including the Geometry Creation Assistant. This hub is the engine room behind it: the use cases that arrive as families, series and repeatable jobs rather than as conversations.
Which modeling operations the AI itself runs inside a live NX session, and how each one is tested to stay an editable feature, is described on our page about AI CAD modeling in Siemens NX.
// One discipline, one shape: defined input, AI engine, human gate, parametric output
Your data, your rules
- Norms & works standards
- Existing NX models & families
- Master templates & tables
- Legacy drawings
NXOpen functions & pipelines
- Rule-based PMI preparation
- Instruction-driven edits
- Template-based part generation
- Batch or selective runs
Engineer decides
- Previews & diff lists
- Confidence per result
- Flagged items to queue
- Nothing commits itself
Parametric, always
- Real features & sketches
- Named expressions
- Semantic PMI
- On your templates
The shape never changes; only the engine does. Whether the run generates PMI, edits geometry or instantiates a template, it enters through your rules, passes a human gate, and leaves parametric.
Three engines, one discipline
Each use case is its own service page with its own demo, honest limits and fixed-scope PoC — scoped as functions and workflows your team runs, not conversations it has to hold:
Three more services create native NX geometry from what you already have: supplier STEP files, legacy drawings, or a plain request in your live NX session.
Functions and workflows — deliberately not a chatbot
Runs as jobs, recipes and pipelines
Defined inputs, encoded rules, repeatable runs over tens to thousands of parts — with review queues where volume demands them. The right shape when the work is systematic.
trigger: a job or a rule · volume: families & archives
NX AI Assistants & Chatbots
The same discipline driven conversationally, one part at a time — e.g. the Geometry Creation Assistant for ad-hoc parts described in a sentence. Chat there, engines here — most teams end up using both.
trigger: a request · volume: the part in front of you
Honest limits
Parametric as far as the model carries. “Fully parametric” is a promise about our output format, not magic: on clean inputs the pipelines produce clean feature trees; on ambiguous geometry, results land in the review queue with their confidence stated instead of being committed quietly. The review gate is mandatory by architecture — no run commits its results without an engineer’s release, because generated PMI and modified geometry carry the same liability as hand-made work.
And a rule the AI can follow is a rule you can write down. Each PoC starts by encoding the relevant slice of your norms and templates — that work is honest effort, and it is exactly what makes the results defensible. Where a job is fully deterministic with no AI judgement needed, we say so and route it to plain NX workflow automation, which is cheaper.
Every engine starts as a bounded PoC — one part family or one workflow, your rules, your infrastructure, measured results (€12,000–€16,500 depending on the engine). Creditable against a rollout.
Talk to an EngineerFrequently asked questions
What is AI-assisted geometry creation?
How is this different from your NX AI chatbots?
Is the output really parametric — or converted lumps?
Who is responsible for generated PMI or modified geometry?
Where does it run — our CAD data is under NDA?
When is plain workflow automation the better buy?
Pick the dullest job in your backlog — the 37th variant or the hundredth routine callout. That’s our favourite demo.
Send us one family part plus the table or norm that drives it — we’ll return prepared PMI or generated variants on your own data, measured against your manual process.
Talk to an EngineerPoCs from €12,000 · fixed scope · creditable against rollout · on-premises option
