Siml.ai

Siml.ai is a web-based platform by DimensionLab for creating, training, and deploying high-performance AI-based numerical simulators. It combines machine learning with physics simulation to deliver real-time, interactive, and highly scalable simulation capabilities through two main components: Model Engineer and Simulation Studio. The platform aims to simplify complex HPC/ cloud workflows and democratize access to physics-based simulation tools.

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How Siml.ai Works

1. Model Engineer: Design and train fast physics simulators using deep learning techniques via a web-based interface. It supports building reusable model architectures and allows dataset management by importing classical simulation exports or real-world sensor data.
2. Simulation Studio: Use trained AI simulators to build interactive, physics- and data-driven digital twins. Visualize results in real time with high-fidelity rendering powered by Unreal Engine, enabling near-instant feedback on the simulated phenomena.
3. Compute & Deployment: Automates high-performance computing tasks, including one-click access to A100 GPUs and deployment to cloud or HPC environments. This streamlines the process of training, optimizing, and running large-scale simulations.

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Key Capabilities

• Web-based access with no local installations required
• Two-part platform: Model Engineer (model creation/training) + Simulation Studio (interactive execution and visualization)
• Datasets management for large-scale simulation data and sensor measurements
• Rapid model development with editable building blocks and customizable code editor
• Automated HPC integration: one-click GPU provisioning (A100s) and scalable cloud/HPC infrastructure
• Ultra-fast simulations via neural network-based surrogates (speedups of 1,000–100,000x over traditional solvers)
• Real-time, in-situ visualization with low-latency feedback
• High-fidelity 3D rendering through Unreal Engine for clear, publication-quality visuals
• Digital twin capability for engineering and scientific problem-solving
• Community and outreach channels (Discord, newsletters) and incentives for early adopters

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How to Use Siml.ai

1. Access Model Engineer to design and train your AI-based physics simulators. Create or import dataset sources from classical simulations or real measurements.
2. Define Building Blocks: Assemble model architectures and constraints using the provided components, with optional code customization for advanced users.
3. Train & Optimize: Leverage GPU-powered cloud/HPC resources to train your learnable simulators, then optimize for accuracy and speed.
4. Move to Simulation Studio: Deploy trained models to solve engineering/scientific problems and construct interactive digital twins.
5. Visualize & Iterate: Use real-time visualization to analyze results and iterate the model or simulation parameters as needed.

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Safety and Considerations

• This tool targets engineering, scientific research, and product development use cases. Users should ensure proper validation of AI-based simulators before critical decisions.
• Access to GPUs and cloud/HPC resources may incur costs depending on usage.

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Core Features

• Web-based platform with no installation required
• Two main modules: Model Engineer and Simulation Studio
• Fast AI-based physics simulators trained via deep learning
• Dataset management from simulations and real sensors
• Build blocks and editable code for custom model architectures
• Automated high-performance computing with one-click A100 GPU access
• Digital twin creation for interactive engineering/science problems
• In-situ, real-time visualization with Unreal Engine rendering
• 1000x–100,000x speedups compared to classical solvers on GPUs
• Accessible via web interface and community resources (Discord, newsletter)

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Additional Details

• Company: DimensionLab (Siml.ai)
• Locations: Lomnická 2, Košice, Slovakia
• Contact: [email protected]
• Policies: Terms & Conditions, Privacy Policy, cookies notice