Technology
Proprietary AI Infrastructure

Powered by Computer Vision.

Motocatch runs on a custom-trained detection engine built specifically for Indian road conditions — handling noisy videos, degraded plates, and crowded traffic scenes with high accuracy.

96%+
Plate Read Accuracy
<3s
Detection Latency
10+
Violation Types
100%
Reporter Anonymity
Core Technology

A Detection Engine Built for Indian Roads.

Our proprietary AI model is trained on millions of real-world Indian traffic scenarios — from busy intersections to rural highways — handling low-light footage, motion blur, and partial plate occlusion.

Deep Learning Architecture

Custom-trained neural networks optimized for Indian vehicle types and plate formats.

Computer Vision Pipeline

Multi-stage processing for vehicle detection, tracking, and violation classification.

Real-Time Processing

Instant analysis from submission to officer dashboard in under 3 seconds.

AI Detection
Vehicle Detected
MH 02 AB 1234
No Helmet (97%)
Detection Output
Complete
Plate Confidence 96.4%
Violation Confidence 97.1%
ANPR Engine
INPUT: degraded plate image
MH ?? A? 1?34
Low confidence — processing...
OUTPUT: enhanced extraction
MH 02 AB 1234
Confidence: 96.4%
Hindi
Script
English
Script
IND
Format
ANPR Technology

Reads Plates Others Can't.

Our Automatic Number Plate Recognition (ANPR) system is trained specifically on Indian plates — including damaged, dirty, and partially obscured plates across all state formats.

Degraded Plates
Handles faded, muddy, and damaged number plates effectively.
Low-Light Video
Processes footage captured in dusk, dawn, and night conditions.
All State Formats
Recognises all 36 Indian state and UT plate formats.
Moving Vehicles
Extracts plate data from mobile-shot footage of moving vehicles.

Detects What Matters.

Motocatch is trained to recognise the most common and dangerous traffic violations on Indian roads.

No Helmet

Detection of riders and pillion passengers without helmets, including partial helmet use.

Triple Riding

Identification of three or more persons on a two-wheeler, a common road safety violation.

Mobile Use While Driving

Detection of drivers operating mobile phones while in motion on public roads.

Wrong Lane / Wrong Way

Flagging of vehicles travelling against traffic or in restricted lanes.

Seatbelt Violations

Detecting car occupants not wearing seatbelts in moving or stationary vehicles.

More Coming

Continuously expanding violation categories based on enforcement team feedback and data.

Privacy-First by Design.

Every report submitted through Motocatch is anonymized at the point of capture. Citizen identity is never exposed at any stage of the enforcement workflow.

End-to-End Encryption

All video evidence and metadata is encrypted in transit and at rest using AES-256 standards.

Identity Anonymization

Reporter identity is cryptographically separated from the report before it enters the review pipeline.

GPS Timestamping

Every piece of evidence is securely timestamped with exact GPS coordinates to ensure legal validity.

Connects With What You Already Use.

Motocatch integrates directly with existing traffic enforcement systems — no new hardware, no disruption to current operations.

e-Challan Integration

Approved cases are routed directly into state e-Challan systems via secure APIs, enabling fast and traceable enforcement.

Operations Dashboard

A centralized review interface for traffic officers to manage cases, view analytics, and monitor enforcement activity.

Secure API Access

Well-documented REST APIs allow integration with traffic management systems, smart city platforms, and data analytics tools.

Mobile-First Reporting

The citizen-facing app works on all Android and iOS devices with minimal data usage, even on 3G networks.

Technology background

See the Technology In Action.

Book a technical demo and see how Motocatch processes real traffic footage in under 3 seconds.