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The Synthetic Stack for Image Intelligence
Beyond What Exists

Synthetic Engine for Computer Vision

Unlimited perfectly labeled data. Zero real-world limits. Generate → Validate → Scale your way to superior models.

Unlimited Scale

Generate millions of diverse samples instantly. Break free from real-world collection costs, delays, and geographic restrictions. Scale effortlessly to train more robust models faster.

Pixel-Perfect Labels

Every annotation (bounding boxes, segmentation, depth, keypoints…) is generated automatically with 100% accuracy and consistency. Slash labeling time & cost while eliminating bias and fatigue.

Edge Cases

Design and control rare, dangerous, or never-before-seen scenarios (extreme weather, sensor failures, rare defects…). Achieve near-perfect coverage of the long tail that real data can’t reach.

our data types

Synthetic data specialized for real-world AI challenges. We provide tailored, high-fidelity datasets that solve scarcity, privacy, and edge-case problems across domains.

Synthetic Satellite & Earth Observation Data

For geospatial AI, remote sensing, change detection, and environmental monitoring

Generate unlimited high-resolution satellite-like imagery with full control over:

Weather/lighting conditions
Seasonal & temporal variations
Sensor types (optical, SAR/radar, multispectral)
Annotations: pixel-level land cover, object detection, change masks

Perfect for training models that need rare events (floods, deforestation, illegal activity) without real satellite costs or access restrictions.

Synthetic Objects for Detection & Segmentation

For robust object detection, instance/semantic segmentation, 3D perception

Create photorealistic scenes with arbitrary objects, poses, lighting, occlusions, backgrounds, and camera angles — always with pixel-perfect annotations:

Bounding boxes
Segmentation masks
Depth & keypoints
Class & attribute labels

Ideal for robotics, autonomous systems, industrial inspection, retail — especially when real data is scarce, biased, or privacy-sensitive.

Synthetic Text Data for OCR, Scene Text & Vision-Language Models

For robust OCR, scene text detection/recognition, layout analysis, and VLM fine-tuning

Generate realistic text in two key domains – fully controllable and always perfectly annotated (character-level, word/line bounding boxes, transcription, key-value pairs):

Structured documents: invoices, receipts, forms, IDs, contracts with realistic noise, folds, skew, lighting, stamps, handwriting, multi-language support.
Natural scene text: text in the wild such as bus stops, street signs, posters, billboards, shop windows, packaging, graffiti, vehicle plates – with diverse angles, distortions, weather effects, lighting conditions, and occlusions.

Train models that excel on both clean scanned documents and challenging real-world text without privacy risks or collection hassles.

Partners

contact us

Want to know more? Contact us and learn how we can help you!

We look forward to hearing from you.

contact@vypno.com

Lichtenbergstr. 8
85748 Garching
Germany

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Legal Notice

Angaben gem. § 5 TMG

Vypno GmbH
Lichtenbergstraße 8
85748 Garching

Registergericht: Amtsgericht München,
HRB: 251315
Geschäftsführer: Maximilian Jakasovic

Telefon: +49 175 1141726
Email: contact@vypno.com

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The Synthetic Stack for Image IntelligenceBeyond What Exists