SYNETIC.ai
Machine-Learned Humor
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The Only Computer Vision AI With A Performance Guarantee
Our synthetic training data is 34% more accurate than real-world datasets (university-verified). If it doesn’t outperform your current approach, get a full refund. Delivered in weeks, not months.
Trusted by defense contractors, manufacturers, and security companies
Traditional vs. Synetic: The Clear Winner
Same training goals, completely different results
Traditional Approach
Time to Deploy
6-18mo
Typical Accuracy
70-85%
Dataset Cost
$500k+
Label Accuracy
~90%
Synetic Approach
Time to Deploy
2 weeks
Typical Accuracy
90-99%
Dataset Cost
$25k
Label Accuracy
100%
10-40x Faster, 90% Cheaper, 34% More Accurate
Our synthetic training data is university-verified to outperform real-world datasets. If it doesn’t beat your current approach, get a full refund.
See The Platform In Action
From data generation to real-time deployment—here’s how it works
Generate Training Data
Control every parameter: lighting, weather, camera angles, actors, and more. Generate unlimited variations with perfect labels automatically.
Perfect Annotations
Every image includes pixel-perfect annotations: bounding boxes, segmentation masks, depth maps, keypoints, and complete camera metadata.
Photorealistic Quality
Physics-based rendering creates images indistinguishable from real-world data—no “domain gap” to overcome.
Deploy Anywhere
See your models running in real-time. Our platform handles edge deployment, cloud inference, and continuous monitoring.
Peer Reviewed Research
34% Better Performance. 100% Synthetic Data. University-Verified.
We didn’t just claim it works—we proved it. In partnership with the University of South Carolina, we trained models exclusively on synthetic data and tested them on real-world images.
The Results: Consistent Improvement Across All Architectures
| Model | Real-only mAP | Synetic mAP | Improvement |
|---|---|---|---|
| YOLOv12 | 0.240 | 0.322 | +34.24% |
| YOLOv11 | 0.260 | 0.344 | +32.09% |
| YOLOv8 | 0.243 | 0.290 | +19.37% |
| YOLOv5 | 0.261 | 0.313 | +20.02% |
| RT-DETR | 0.450 | 0.455 | +1.20% |
Seven different model architectures tested. All showed improvement with synthetic training data.
Validated on real-world test set. Full methodology peer-reviewed by USC researchers.
Download the Full Study
Synthetic Models Detect What Humans Miss
Ground Truth (Incomplete)
Human labels miss several apples
Real-Trained Model
Misses apples, limited detection
Detects all apples, including those missed by humans
Synetic-trained models (right) detected all apples, including those missed in the human-labeled “ground truth” (left). Real-trained models (center) missed multiple apples. What appears as false positives in our model are actually correct detections.
“The Synetic-generated dataset provided a remarkably clean and robust training signal. Our analysis confirmed the superior feature diversity of the synthetic data.”
Dr. Ramtin Zand & James Blake Seekings
University of South Carolina
Choose Your Solution
Get exactly what you need—from data to fully managed deployment
Synthetic Training Data
We generate it, you train it
Perfect for: ML teams, researchers, consultancies
$30,000
$15,000*
Validation Challenge pricing
Custom Trained Models
We build it, you deploy it
Perfect for: Companies with deployment capability
$50,000
$25,000*
Validation Challenge pricing
Enterprise Solution
Fully managed computer vision platform
Perfect for: Ongoing partnerships or custom deliverables
Custom
Validation Challenge pricing
*Typical prices. Prices may vary with requirements
Help us expand the evidence base for synthetic data superiority.
Get 50% off our services while building the future of computer vision together
What is This Program?
Our University of South Carolina white paper proved synthetic data outperforms real-world data by 34% in agricultural vision. Now we’re expanding that proof across industries.
We’re inviting 10 pioneering companies to deploy Synetic-trained computer vision systems at a significant discount, in exchange for allowing us to document your results as case studies.
Your success story becomes validation that synthetic data works across defense, manufacturing, autonomous systems, and beyond—not just agriculture.
Why Participate?
50% Discount
Get our full service offerings at half price during this validation period
Early Adopter Status
Be among the first companies to deploy proven synthetic-trained AI in your industry
Independent Validation
Your results contribute to peer-reviewed research validating synthetic data
Thought Leadership
Be featured as an innovation leader in published case studies and whitepapers
Proven Across Industries
See your models running in real-time. Our platform handles edge deployment, cloud inference, and continuous monitoring.
Manufacturing QC
Detect defects before production starts
Agriculture
Automate crop detection and yield estimation
Security
Identify threats and anomalies in real-time
Robotics
Train perception models entirely in simulation
Retail Analytics
Track inventory, customers, and behaviors
Logistics
Monitor safety, packages, and operations
Frequently Asked Questions
How can synthetic data be better than real? Real-world datasets are limited by what you can photograph and afford to label. Ours cover edge cases systematically, with perfect labels. The USC white paper proves it: +34% better performance across multiple architectures.
Will models trained on synthetic data work on my real cameras?
Yes. Our physics-based rendering ensures synthetic and real data are statistically similar. There’s no “domain gap”—the 34% improvement was measured on real-world validation data, not synthetic tests.
How long does it actually take?
1 week for datasets, 2 weeks for custom trained models, 1 week for deployment. Compare that to 6-18 months for traditional real-world data collection.
What if my use case is unique?
That’s exactly what we’re built for. Tell us what you need and we generate the training data custom for you. We’ve built 150+ models across dozens of industries. If you can describe it, we can generate it.
Do I need to provide my own data?
No. We generate everything synthetically. You can add real data later if you want, but it’s not required (and the white paper shows it actually hurts performance).
What’s included in the money-back guarantee?
If our synthetic-trained model doesn’t meet or exceed your expectations (or doesn’t outperform your existing real-world trained models), we refund 100%. We’re that confident.
Ready to build better models?
Join the validation challenge: 10 spots available at 50% off with 100% money-back guarantee
Questions? Email sales@synetic.ai or schedule a 15-min call