A generative AI companion for visual outdoor synthetic data

Majestic.ai generates synthetic data across all sensor types and spectrum ranges, from visible light to thermal IR, LiDAR, and SAR, using precise physics-based models for AI/ML engine training and validation.

By delivering annotated visual datasets in realistic, controlled outdoor environments, Majestic.ai significantly accelerates research and development, reduces training and validation costs, and shortens delivery times substantially.

Features and Capabilities

Full Spectral simulation

Full Spectral simulation

  • VIS / NIR / NVG / SWIR / MWIR / LWIR
  • Multi/Hyper spectral
  • LiDAR
  • SAR

Datasets as a Service (DaaS)

Datasets as a Service (DaaS)

  • Delivery of Video and Images
  • Fast delivery accelerating Go-To-Market
  • Enables data scientists, researchers and developers to focus on AI development

Environment

Environment

  • land, maritime, air and space environments

Datasets verification

Datasets verification

  • Boundary boxes and objects contours
  • Classification and segmentation
  • Statistics and per image metadata
  • Standard formats (COCO, YOLO, etc.)

Automatic annotation and metadata

Automatic annotation and metadata

  • Boundary boxes and objects contours
  • Classification and segmentation
  • Complete sensor and scene description per image
  • Dataset statistics
  • Standard formats (COCO, YOLO, etc.)

Reduce costs

Reduce costs

  • Minimizes real data acquisition
  • Optimize human resources
  • Fast delivery
  • Privacy & security

Widely diverse & balanced datasets

Widely diverse & balanced datasets

  • Randomizing parameters
  • Control over scenario parameters
  • Dynamic thermal behavior
  • Complex scenes, multiple models, dynamic behavior

AI engine validation

AI engine validation

  • Annotated video & images for AI validation
  • Replacing real videos & images when scarce, costly, or time-sensitive
  • Progression, boundary, negative and load testing

Media

Download Documents

Majestic.ai Brochure

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