Auto-labelling.
Do It Right.

This is a Survey website and will work exactly like our main website.
Move Faster. Labelling without limits. Universal precision for your data.

The Anatomy of Accuracy

Precision universalism over generic detection

The Other Way
Object Detected
Confidence: 60%
Method: Blurry Bounding
The Demo Labelling Way
Auto_Rickshaw
Confidence: High Precision
Method: Pixel-Perfect Segmentation

Why Demo Labelling?

Traditional methods are broken. We built the alternative.

Generic

Pre-trained Models

Trained on someone else's data

  • Trained on irrelevant, generic datasets — not yours
  • Low accuracy for niche or domain-specific projects
  • Heavy compute usage & slow inference speed
  • Cannot adapt to your unique object classes
  • Zero customisation — one-size-fits-none approach
Outdated

Manual & Semi-Manual

Human-powered, human-limited

  • Extremely high cost per image — burns your budget fast
  • Weeks or months of turnaround time per project
  • Human fatigue leads to inconsistent, error-prone labels
  • Semi-manual tools still require heavy human oversight
  • Near impossible to scale instantly to thousands of images
The Solution

Demo Labelling

Built for your data. Automated for speed.

  • Custom model trained on your requirements
  • Fully automated SAM-3 pipeline — zero manual effort
  • 500,000 images or 5-minutes videos in minutes
  • Pixel-perfect segmentation at 97%+ precision
  • Works across all domains — urban, aquatic, botany & more

Universal Genome

Beyond standard detection - achieving precision across all domains

Urban Intelligence

Vehicles & Humans

Beyond standard cars; includes Global South specifics and dense pedestrian crowds

Biological Precision

Animals

High-fidelity bounding for wildlife and livestock across diverse environments

Aquatic Mapping

Fishes

Specialized segmentation for underwater visibility and marine species

Botany & Agriculture

Plants

Fine-grained leaf and crop segmentation for precision ag-tech

Multi-Format Engine

Universal Processing

Process Video, Image, and GIFs natively with unified pipeline

The Intelligence Factory

From chaos to precision in 6 stations

01

Universal Ingestion

Auto-format normalization

→
02

Context Aware Trigger

Identifies forest, city, or ocean

→
03

Hybrid Bounding/ Segmentation

Simultaneous logic

→
04

Edge Case Refinement

Secret sauce for precision jump

→
05

Quality Gate

Validation layer

→
06

Universal Export

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Precision Comparison

See the difference: Bounding Box vs. Pixel-Perfect Segmentation

BOUNDING BOX

Bounding Box Example

Captures empty space

Bounding Box
~70% Precision
Includes background noise
Bounding Box
Segmentation

Secret Laboratory.
Public Good.

Precision universalism for everyone. Zero compromises.