Curlscape AgentCrew & Curlscape Sift
AI platforms purpose-built for engineering and simulation teams. Deploy agents that prep CAD, mesh, and set up solvers — and surrogate models that turn weeks of simulation into minutes.
Curlscape AgentCrew — Agentic AI for Engineering Workflows
Deploy AI agents that handle the repetitive layers of simulation work — geometry preparation, meshing, solver setup — so your engineers spend their time on actual engineering. Launch parallel agents with planning and end-to-end orchestration, and multiply the throughput of your CAE team.
The agent lineup:
- Planning agents.
- Complex simulations demand upfront planning across physics, assumptions, prior comparable runs, and test data. Planning agents assimilate this context through smart connectors, produce a structured simulation plan, and execute it autonomously — or iterate on it with you.
- CAD agents.
- Clean, simulation-ready geometry (watertight for CFD; defeatured and well-connected for FEA) is the prerequisite for reliable results. CAD agents automate cleanup with both the analyst's simulation intent and the CAD engineer's tool knowledge built in.
- Meshing agents.
- Encode meshing best practices and iterate autonomously against your target quality metrics — running until the mesh meets spec.
- Solver setup agents.
- Wrong boundary conditions, operating conditions, and physics setup sink a significant share of simulations. Setup agents encode experienced-engineer judgment so simulations launch right the first time.
- Reporting agents.
- Engineering reports generated automatically, following your formatting standards and required content.
Connectors — how AgentCrew works with your stack
An agent is only as useful as what it can read and act on. Connectors are how AgentCrew plugs into your existing toolchain — no rip-and-replace, no vendor lock-in.
Every connector does two jobs:
- Read context.
- Pull in the material an agent needs to plan and decide — geometry and model files, simulation setups, past runs, mesh quality reports, test data.
- Execute actions.
- Drive the tool itself through its scripting and API layer — running cleanup operations, generating meshes, configuring solvers, launching runs.
Current coverage:
| Domain | Commercial | Open source |
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| CAD |
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| Meshing |
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| Solvers |
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Don't see your tool? Connectors are built to demand. If your stack includes a tool we don't cover yet, we scope the connector as part of your pilot — most take days to weeks, not months, because the agent architecture is tool-agnostic by design.
Curlscape Sift — Surrogate Modeling & Model Order Reduction
Surrogate models compress the design cycle by orders of magnitude — simulation results in minutes instead of hours or weeks — and finally put your legacy simulation archives to work as training data.
- Neural operator surrogates.
- Import simulation data, visualize, configure, train, and monitor in one interface. Leading architectures from NVIDIA and Emmi AI — DoMINO, AB-UPT, MeshGraphNet — in a single unified platform.
- ML-based model order reduction.
- For edge deployments and cases where full 3D fields aren't needed: lightweight ML surrogates, plus digital twin models like prognostics and RUL estimation using Bayesian techniques.
- Multi-fidelity modeling.
- Fuse many fast low-fidelity runs (e.g., BEMT for propeller design) with a few high-fidelity CFD runs via co-kriging — near-CFD accuracy across the full design space at a fraction of the cost.