VoxelDyn Labs synthesizes production-grade 3D meshes, 4D Gaussian Splats, and volumetric spatial digital twins in under 4 seconds via scalable cloud APIs.
Across game studios, AR apps & robotics
Direct edge inference on AWS Inferentia
Enterprise clusters with zero single-point failure
Developing with VoxelDyn REST & Python SDK
Whether you are designing robotic perception systems, AAA game environments, or real-time spatial digital twins, VoxelDyn Labs provides the foundational AI infrastructure.
Convert natural language descriptions into production-ready 3D meshes with clean quad topology, UV unwrapping, and 4K PBR material maps in seconds.
High-fidelity dynamic scene reconstruction from sparse multi-view video feeds. Generates real-time view-dependent radiance fields at 120+ FPS.
Unified REST, gRPC, and Python SDKs designed for developers. Seamlessly integrate automated 3D pipeline workflows into existing CI/CD stacks.
Synthetic training environment generation for robotic arms, quadrupeds, and autonomous drones. Export directly to Isaac Sim, MuJoCo, and Gazebo.
Engineered natively on Amazon Web Services. Scaling automatically on Amazon EC2 P5/G5 GPU instances, Amazon S3 high-speed storage, and SageMaker.
Multi-tenant data isolation with zero customer data training policies. Fully encrypted in-transit (TLS 1.3) and at-rest (AES-256) with SOC2 readiness.
Our SDKs abstracts complex GPU orchestration, voxel diffusion, and 3D format conversion. Integrate directly into your web applications, mobile AR apps, or robotic automation pipelines.
import voxeldyn
# Initialize VoxelDyn client (AWS accelerated inference)
client = voxeldyn.Client(api_key="vox_live_8f3d82a7...")
# Generate high-resolution 3D asset from text prompt
response = client.models.generate(
prompt="Futuristic autonomous delivery drone with dual lidar sensors",
format="gltf",
polycount=50000,
texture_resolution=2048,
aws_cluster="us-east-1"
)
print(f"Generated Asset ID: {response.asset_id}")
print(f"Direct S3 Mesh URI: {response.mesh_url}")
# Output: -> Completed in 3.84s (Inference: AWS EC2 G5.4xlarge)Transparent pricing based on actual generative 3D inference workloads on high-throughput AWS GPU clusters.
VoxelDyn Labs leverages Amazon Web Services accelerated compute and custom CUDA 12.6 kernels to deliver deterministic sub-40ms spatial inference worldwide.
High-density NVIDIA H100 and A10G GPU clusters provisioned across multi-AZ regions for uninterrupted diffusion model training and high-throughput inference.
Purpose-built silicon for generative AI with 4x higher throughput and up to 50% lower cost per inference compared to standard GPU instances.
Petabyte-scale distributed object storage for generated 3D meshes, Gaussian point clouds, and multi-view video training datasets with 11 9's durability.
Global content delivery network caching static 3D GLTF files and API metadata within 15ms of 98% of the world's connected population.
See how forward-thinking studios and robotics teams build with VoxelDyn Labs.
"VoxelDyn Labs cut our 3D environment synthesis pipeline from 3 days of manual 3D modeling to 30 seconds of automated API execution. The quad mesh topology is astonishingly clean."
"We use VoxelDyn's 4D Gaussian Splatting engine to generate dynamic spatial twins of industrial manufacturing cells. The sub-40ms latency on AWS makes real-time robot actuation possible."
"The Python SDK and USD export options allowed our e-commerce 3D catalog team to generate 150,000 spatial product models with photorealistic textures in under two weeks."
Everything you need to know about the VoxelDyn platform and developer API.
Sign up now for 100 free monthly generation credits. Deploy into production with our Python SDK in under five minutes.