Simbotic

An advanced simulation platform that bridges virtual and physical worlds, enabling AI systems to learn through realistic interaction and environmental understanding.

While large language models have revolutionized AI, they often struggle with physical reasoning and three-dimensional understanding. Real-world robotics and autonomous systems require spatial perception, motion prediction, and the ability to learn from physical interaction.

Simbotic provides the infrastructure for AI to develop these capabilities through high-fidelity digital twins and unlimited synthetic training scenarios, accelerating the path from simulation to real-world deployment.

Epic MegaGrants Recipient

Simbotic has been accelerated by Epic MegaGrants funding. We're actively developing plugins, extensive documentation, and tutorials. Contact us to explore how Unreal Engine 5 can transform your robotics, AI training, or autonomous systems projects.

TRAINING ENVIRONMENTS

Simbotic creates dynamic multi-agent environments where AI learns to navigate, manipulate, and reason about physical spaces. From physics simulations that teach mechanical understanding to photorealistic scenes that train computer vision systems.

These environments allow AI to develop crucial capabilities: understanding object relationships, predicting trajectories, planning movements, and learning from trial-and-error. These are skills that language models alone cannot provide.

With perfect ground-truth data and infinitely configurable scenarios, complex behaviors that would take years to learn in reality can be mastered in days of accelerated simulation.

Synthetic Data

When real-world data is scarce or dangerous to collect, Simbotic generates unlimited synthetic datasets from virtual scenarios that mirror reality with precise accuracy.

Through domain randomization (varying lighting, textures, and physics parameters), AI models learn to generalize beyond specific scenarios, developing robust capabilities that transfer seamlessly to the real world.

Leveraging generative AI including diffusion models and neural radiance fields (NeRFs), Simbotic creates diverse 3D environments and assets, exponentially expanding training possibilities.

Human-AI Collaboration

Humans and AI work together in a powerful feedback loop. Expert operators can demonstrate complex behaviors, correct mistakes, and teach nuanced skills that pure automation struggles to discover.

By stepping into simulations, humans can guide AI through challenging scenarios, demonstrate optimal strategies, and transfer years of expertise in minutes. This dramatically accelerates the learning process.

This collaborative approach is essential for developing trustworthy autonomous systems that can handle edge cases, adapt to unexpected situations, and align with human intentions and values.

Accelerated Pipelines

Powered by Unreal Engine 5 for stunning visual fidelity, NVIDIA technologies for GPU acceleration, and PyTorch for deep learning, Simbotic delivers the computational performance needed for real-time AI training.

Custom streaming pipelines built with GStreamer and performance-critical components in Rust ensure minimal latency between simulation and learning, enabling real-time decision making even in complex multi-agent scenarios.

Fully containerized and Kubernetes-ready, Simbotic scales from single experiments to massive parallel training runs, bringing enterprise-grade reliability to AI development workflows.

ThirdParty Integrations

Facilitates bidirectional interfacing with prominent media and robotics ecosystems to extend LLM capabilities.

Second Image — ROS 2 URDF with RViz visualization for spatial and embodied AI

CONTACT

info@vertexstudio.co