Unlimited Synthetic Training Data for Computer Vision
When real-life image capture is challenging,
AI Verse Procedural Engines generate synthetic image datasets in hours!
What Is Synthetic Training Data for Computer Vision?
Synthetic training data is artificially generated imagery: built from 3D models, physics-based rendering engines, and procedural algorithms that replicate real-world visual conditions without requiring cameras, field teams, or labeling contractors.
For computer vision engineers, the bottleneck has never been the model architecture.
It’s the data. Collecting real imagery at scale requires access to environments that are expensive, dangerous, or, in defense and autonomous systems applications, operationally impossible.
Annotating that imagery adds weeks: a 100,000-image defense dataset with 8 annotation types typically costs $80,000–$150,000 in manual labeling, takes 6–12 weeks, and requires security clearance when handling classified scenes.
Why choose Synthetic Training Data for CV?
AI Verse procedural technology ensures the highest quality, unbiased, labeled synthetic datasets that will improve computer vision model’s accuracy
On Demand
Generate the images when you need them.
Customizable
Gain complete control over configurations, including scenes, sensors, lighting, activities, labels, and more.
Privacy Compliant
Eliminate privacy concerns by avoiding the use of real-world data.
How AI Verse Generates Synthetic Training Data
Procedural engine
AI Verse’s procedural engine eliminates computer vision data bottleneck.
Define your parameters: object classes, environments, lighting, sensor type, weather, viewpoint, etc., and the platform generates fully annotated images in 4 seconds on 1 GPU, at any scale, with pixel-perfect annotation.
PROCEDURAL SCENE GENERATION
Scene Layout: Stochastic Decomposition Trees
3D Standardized Assets Database
3D SCENE
IMAGE
RENDER
Complex Labelling
Materials Database
Light Sources
Virtual Camera Controls and Properties
RGB, Infrared And Pixel-Perfect Labels for Every Computer Vision Model
With AI Verse’s procedural engine, training datasets that once took teams three months to build can now be completed in hours. And unlike real-world data, any scenario; adverse weather, rare object configurations, sensor failures, edge cases; can be generated on demand.
Eliminate the need for slow, costly real-world data collection and annotation
with AI Verse Indoor and Outdoor Procedural Engines:
HELIOS
Procedural Engine That Generates Indoor Synthetic AI-Ready Image Datasets
Access Unlimited Synthetic Image Datasets
to Train Your Computer Vision Models!
GAIA
Procedural Engine to Generate Outdoor Synthetic AI-Ready Image Datasets
Trusted by Computer Vision engineers in Top NATO countries Companies
Generate Fully Labeled Synthetic Image Datasets with Gaia
and Accelerate Your AI Training!
Scale AI Training and Deployment
Cut Cost & Time on Data Acquisition
Generate one fully labeled image in just 4s!
Enhance AI Model Accuracy
Generate all edge cases to improve your models’ accuracy!
Obtain Pixel-Perfect Labels
8 Annotation Types. Zero Manual Labeling
Accelerate
Time-to-Market
Launch faster than ever before and gain a competitive edge!
Use Cases
Built for Defense, Drone, Smart Home and other CV Applications
FAQs
What Pixel-Perfect Labels Are Included in AI Verse's Synthetic Image Generation Engine?
There are 8 pixel-perfect labels included: Classes, Instances, Depth, Normals, 2D/3D Bounding Boxes, 2D/3D Keypoints, Skeletons, and Color.
How Does AI Verse Generate Synthetic Data for AI Model Training?
Users select the desired parameters for the environment, scenes, objects, activities, lighting, and more. Based on these criteria, our engine can generate an unlimited number of diverse, varied, and labeled images ready for AI model training.
How Accurate Are the Labels in AI Verse's Synthetic AI Datasets?
Yes, our automated system ensures that each generated image contains 8 pixel-perfect labels, reducing the risk of inaccuracies and guaranteeing the highest data quality.
What Is The Difference Between AI Verse Synthetic Image Data and GenAI Images?
Our proprietary procedural technology generates images based on human input. Users select various criteria for the image from a menu in a step-by-step process, rather than typing a prompt into a GenAI tool. This approach minimizes mistakes and ensures the highest possible realism in our images.
How fast do you generate images?
It takes 4s to generate one labelled image on 1 GPU. Generation can be spread across several GPUs (max 10).