Train a Computer Vision model without ever touching a 3D tool

We handle the 3D modeling, asset variation, rendering, annotation, and training, so you don’t have to. Just tell us what you need your model to recognize.

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“Synetic helped us deploy a fully functioning model in 10 days, no real-world images needed.”

— Director of AI, Top 10 Agribusiness

Trained on synthetic, performs in reality

Synetic-trained models don’t just pass benchmarks, they succeed in the wild. Whether it’s detecting crop damage from a moving pivot or tracking a robotic arm in factory lighting, our models are stress-tested for real-world deployment.Starts at 1¢ per image. No manual data labeling. No long waits. Just results.

Generalizes across lighting, motion blur, and background clutter
Consistently matches or exceeds real-data-trained models in performance
Custom-tailored to your inference architecture, including edge devices
Supports continuous improvement with iterative dataset refinement

Transparent pricing. One cent per image.

No hidden fees. No enterprise contracts required. We charge by the image, not by the seat, GPU hour, or “AI readiness.”

$0.01 per image (base)
Bundled model + SDK available
Cancel anytime, scale instantly

Don’t pay $1.70 per image for manual annotation or $0.20 for low-quality generative data. Synetic AI delivers pixel-perfect realism at a fraction of the cost, with full control over what your model learns.

Every plan comes with a 2-week money-back guarantee.

When failure isn’t an option, synthetic data gives you full control, and full confidence.

Trusted by innovators in Vision AI

Our platform supports leaders in agriculture, robotics, industrial automation, and more.

Organizations from AgTech to advanced manufacturing rely on Synetic AI for faster model development, lower cost of ownership, and edge-ready performance.

Whether you’re building models for agriculture, robotics, manufacturing, or surveillance, Synetic AI gives you full control, without the typical bottlenecks of data collection.

Faster iteration cycles with programmatically varied scenes
No privacy concerns or logistics overhead
Pixel-accurate annotations for bounding boxes, masks, and depth
Works with YOLO, RT-DETR, DINOv2, and other top architectures
Backed by millions in R&D and field testing
Used in production by Fortune 500 and early-stage startups alike
Engineered to meet edge deployment constraints

Custom assets, built for your vision

We specialize our growing library of high-fidelity, behavior-aware 3D assets to match your exact specifications. You don’t need any modeling experience — we handle everything behind the scenes.

Custom asset tuning for your objects, environments, and behaviors
Supports humans, animals, vehicles, machinery, crops, and more
Animation-ready characters with physical interactions
No off-the-shelf limitations — we adapt the assets to your exact use case
Your dataset feels bespoke, but benefits from shared infrastructure

This allows us to build your model at no additional cost while continually improving the underlying asset base for future clients.

Real physics. Real lighting. No GAN artifacts.

Our datasets are rendered using physically based simulation, photometric lighting, and procedural variation — not neural style transfer or hallucinated GANs. That means your model learns from scenes that obey the real-world laws of optics, motion, and geometry.

Ray-traced reflections, refractions, and shadows
Domain randomization for lighting, weather, and material properties
Procedural camera setups for motion blur, occlusion, and distortion
Zero GAN artifacts, checkerboarding, or style drift
Engineered for accuracy in depth, scale, and sensor simulation

How Synetic AI works

We turn your concept into a working computer vision model — no 3D tools, annotation labor, or ML expertise required.

Define what to recognize
Specify the object, condition, or behavior you want the model to detect. Be as specific or broad as you like.
We generate the training set
Our engine creates thousands to millions of images, procedurally varied and physically accurate — complete with annotations.
Train the model (optional)
Use our built-in training workflow or export the dataset to train using your own pipeline. We support most popular vision architectures.
Deploy with confidence
Receive weights or an SDK to integrate into your app, edge device, or pipeline — fully tested and ready to go.$0.01 per image (base)

It’s everything you need to get from idea to deployment, minus the months of data collection and tuning.

Why Synthetic Data beats manual labeling

Manual labeling is slow, expensive, and error-prone. Synthetic data eliminates the bottlenecks by giving you control over every variable — without compromising on accuracy.

Pixel-perfect annotation: Bounding boxes, masks, depth maps, and more generated automatically.
Unlimited variation: Randomize backgrounds, lighting, poses, and occlusions to improve generalization.
Scales instantly: Generate thousands to millions of images without hiring a team of labelers.
No privacy risk: No real people, faces, or proprietary settings in your dataset.
Built-in edge cases: Capture rare, dangerous, or unusual events by design.
Outperforms real data: When trained correctly, synthetic models generalize better than real-world collections.

With Synetic AI, you don’t just match the performance of real data — you exceed it, while cutting cost and time by orders of magnitude.

Get started

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Common Questions

Do I need 3D skills or assets? 
Nope. We handle everything.

Can this replace real-world data? 
In most cases, yes. Our datasets are designed to generalize.

How long does it take? 
Most models are ready in days, not months.

Can I use my own models or training pipeline? 
Yes. You can export datasets with full annotations in standard formats and train them using your own tools.

What types of annotations are supported?
We support bounding boxes, segmentation masks, depth maps, occlusion metadata, and instance IDs. 

Do I have to commit to a minimum volume?
No. Start with as little as 100 images and scale up on demand.

Can I simulate rare or extreme scenarios?
Yes. We support rare weather, edge cases, and adversarial conditions through procedural variation.

How is this different from GAN-generated data?
Our data is rendered using physics-based engines, not hallucinated. That means it behaves like reality and generalizes far better.

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