Better Models Deployed Faster With Synthetic Data
A synthetic data platform to enable more capable and ethical computer vision AI.
Better Models Deployed Faster With Synthetic Data
Synthetic data for computer vision to enable more capable and ethical AI.
Trusted by:
On-Demand Labeled Images and Videos
Highly scalable data generation platform delivers millions of perfectly labeled images.
On-demand synthetic data for computer vision offers a new paradigm for developing more performant models.
Photorealistic Images
A unique combination of generative AI, procedural generation, and cinematic VFX rendering systems work together to deliver photorealistic images and video.
3D Generative AI
We provide diverse 3D human models built with generative AI. Turnkey asset libraries are available for licensing, in addition to platform access for creating labeled data on-demand.
Better Labels Better Models
An expanded set of pixel-perfect labels including segmentation maps, dense 2D/3D landmarks, depth maps, surface normals, and much more.
Explore our products
Synthesis Humans
Create detailed images and videos of digital humans with never-before-available rich annotations.
Synthesis Scenarios
Craft complex multi-human simulations across a varied set of environments.
Industries, Applications & Use Cases
ID Verification
Millions of images of unique individuals to build privacy-compliant and unbiased facial ID models.
Automotive - Driver Monitoring
Model complex driver behavior across demographics, car interiors, and camera types.
Avatar Creation
A platform for ML engineers to generate labeled data for developing avatars in consumer, industrial and enterprise applications.
Virtual Fashion
Control over body type, pose, and millions of clothing options to create the most robust models.
AI Fitness
Perfectly labeled pose and body segmentation across body types, activities, environments, and cameras.
Teleconferencing
Pixel-perfect annotations for background segmentation and facial landmark tracking.
Visual Effects (VFX)
Diverse images with detailed labels to build markerless tracking models and virtual green screen applications.
Security
Create multi-person scenarios across environments for activity recognition and threat detection.
Industries, Applications & Use Cases
ID Verification
Millions of images of unique individuals to build privacy-compliant and unbiased facial ID models.
AR/VR/XR
Model complex driver behavior across demographics, car interiors, and camera types.
Avatar Creation
Access to 100K unique identities each with 5,000 facial landmarks for creating the most realistic avatars.
Driver Monitoring
Model complex driver behavior across demographics, car interiors, and camera types.
ID Verification
Millions of images of unique individuals to build privacy-compliant and unbiased facial ID models.
Automotive - Driver Monitoring
Model complex driver behavior across demographics, car interiors, and camera types.
AR/VR/Metaverse
Access to 100K unique identities each with 5,000 facial landmarks for creating the most realistic avatars.
Teleconferencing
Pixel-perfect annotations for background segmentation and facial landmark tracking.
Industries, Applications & Use Cases
ID Verification
Millions of images of unique individuals to build privacy-compliant and unbiased facial ID models.
AR/VR/XR
Human-centric ML models for headset hardware and software development in consumer, industrial, and enterprise applications.
In-cabin Automotive
Model complex driver behavior across demographics, car interiors, and camera types.
Autonomy - Pedestrian Detection
Simulate multi-person scenarios in complex outdoor environments, all with perfect pose and segmentation labels.
Virtual Try-on
Control over body type, pose, and millions of clothing options to create the most robust models.
Teleconferencing
Pixel-perfect annotations for background segmentation and facial landmark tracking.
Security
Create multi-person scenarios across environments for activity recognition and threat detection.
We wrote the book on Synthetic Data
“…our field must tap into rich sources of synthetic and real data. Sergey Nikolenko’s book lucidly surveys the state of the art in the former, and I consider it required reading for any researcher using deep learning based methods.”
Serge Belongie
Department of Computer Science at the University of Copenhagen (DIKU) and Director, Pioneer Centre for Artificial Intelligence
