SimScale launches Engineering AI Agent within Onshape

Key Takeaways

• SimScale’s Engineering AI Agent is now embedded in Onshape, letting designers start a full‑physics simulation with a single natural‑language prompt.
• The agent handles geometry cleanup, mesh generation, physics selection, boundary‑condition setup, execution, and result explanation without leaving the CAD workspace.
• Supported physics: CFD, thermal, electromagnetic (EM), and structural FEA, all running on SimScale’s cloud‑native solver fleet (up to 200 k CPU‑hours per day).
• Compared with the classic export‑to‑solver workflow, the AI‑driven path cuts “simulation‑ready” time by 70 % and reduces overall design‑to‑prototype cycles by up to 7× (as reported by early adopters).
• The solution is delivered through the Onshape App Store, requires only a one‑click enablement, and complies with enterprise audit and data‑governance policies via the SimScale Agent API.

SimScale Engineering AI Agent: What It Does

Natural‑Language‑Driven Simulation

Engineers type prompts such as “run a steady‑state thermal analysis on this housing with a 150 °C heat source” and the agent:

1. Identifies the relevant physics (thermal, CFD, etc.).
2. Prepares the CAD geometry – removes small features, creates watertight bodies, and applies defeature rules.
3. Generates a mesh (default element size 0.5 mm for solid parts, 2 mm for fluid domains).
4. Assigns boundary conditions based on the prompt and best‑practice libraries.
5. Launches the solver on SimScale’s elastic cloud (auto‑scales from 2 to 64 cores).
6. Returns results directly in Onshape, with visual overlays, plots, and plain‑English explanations.

Integrated App Experience

• Installation: One‑click from the Onshape App Store → “Enable”.
• Workflow: The AI panel appears as a docked tab inside any Onshape document.
• Control: Users may edit the auto‑generated setup before execution, ensuring engineering judgment remains central.

How It Differs From Traditional Simulation

Quantitative Impact

• Design‑to‑prototype: Companies such as Withings reported a 7× reduction after moving simulation earlier in the design loop.
• Simulation‑ready time: Average geometry preparation dropped from 45 min to 13 min (≈ 70 % faster).
• Resource utilization: The AI agent automatically provisions compute nodes, achieving 95 % average solver CPU utilization versus ~60 % in manual batch runs.

Architecture & Governance

• SimScale Agent API: Exposes job metadata, resource allocation, and execution logs.
• Auditability: Every AI decision (physics choice, mesh parameters, BCs) is recorded, enabling traceability for regulated industries.
• Security: Data remains encrypted in‑transit (TLS 1.3) and at rest (AES‑256); on‑premise customers can route traffic through private links.

Real‑World Adoption

• User base: Over 900 k engineers worldwide already run CFD, FEA, thermal, and EM analyses on SimScale.
• Case study – Withings: By embedding the AI agent in their product development pipeline, they cut the average iteration cycle from 6 weeks to ≈ 1 week.
• Industry spread: Automotive, consumer electronics, and medical device firms are piloting the solution to accelerate early‑stage validation.

Bottom Line

SimScale’s Engineering AI Agent transforms the traditionally fragmented simulation workflow into a seamless, conversational experience inside Onshape. By automating geometry cleanup, meshing, physics selection, and result interpretation, it slashes set‑up time by up to 70 % and enables design teams to validate concepts days instead of weeks. The cloud‑native, API‑driven architecture ensures scalability, auditability, and enterprise‑grade security, making it a compelling option for any organization looking to embed simulation deeper into the design decision loop.