📊 Stage 1: Data Foundation

Data &
Annotation

High-quality labeled data is the foundation of every successful Vision AI system. We build custom datasets and annotation pipelines tailored to your specific needs.

What We Build

Custom Dataset Creation

  • â–¸Domain-specific data collection strategies
  • â–¸Data augmentation pipelines
  • â–¸Synthetic data generation
  • â–¸Multi-modal dataset design

AI-Assisted Annotation

  • â–¸Semi-automated labeling tools
  • â–¸Active learning workflows
  • â–¸Quality control systems
  • â–¸Multi-annotator consensus

Annotation Types

  • â–¸Bounding boxes, polygons, masks
  • â–¸Semantic & instance segmentation
  • â–¸Keypoint & pose annotation
  • â–¸3D point cloud labeling

Data Management

  • â–¸Version control for datasets
  • â–¸Data pipeline automation
  • â–¸Storage optimization
  • â–¸HIPAA/GDPR compliance

Common Use Cases

Medical Imaging Datasets

Creating annotated datasets for diagnostic AI: organ segmentation, pathology detection, surgical planning with radiologist-verified labels.

Industrial Inspection

Defect detection datasets with pixel-perfect annotations for manufacturing quality control and automated inspection systems.

Autonomous Systems

Multi-sensor datasets (camera + LiDAR) with 3D bounding boxes, tracking IDs, and scene understanding labels for robotics.

Need High-Quality Training Data?

Let's discuss your data requirements and build a custom annotation pipeline.

Schedule Consultation →