Introduction

1. Overview

EYNTRY is an AI-powered vision platform for real-time object recognition and analysis. Designed for scalability and efficiency, it integrates advanced AI models, cloud-based and edge processing, and a user-friendly interface.

Key goals:

• Accessibility: Usable by both AI developers and non-technical users.
• Efficiency: High accuracy in challenging conditions (rain, fog, low light).
• Scalability: Deployable on cloud and edge infrastructures.

EYNTRY bridges the gap between raw visual data and actionable insights, empowering businesses, researchers, and developers to create AI-driven solutions.

2. System Architecture

EYNTRY employs a hybrid cloud + edge AI model for distributed processing. Key components include:

• AI Core: Uses YOLOv8, PyTorch, and TensorRT for high-performance object detection.
• API Gateway: GraphQL and REST APIs for seamless integration.
• Data Management: PostgreSQL and MinIO for structured/unstructured storage.
• Authentication & Security: Keycloak/Auth0 for secure access control.
• Event Processing: Kafka/MQTT for real-time data streaming and automation.
• Monitoring & Logging: Prometheus and Grafana for observability.

This modular architecture ensures adaptability across industries, from smart surveillance to industrial automation and smart cities.

3. Key Use Cases

EYNTRY supports diverse applications, including:

• Smart Surveillance: AI-driven security monitoring.

Case #1 - Road Barrier Access Managment

CASE #2 - Prevent incidents resulting from blind spots

• Industrial Automation: Real-time object recognition for manufacturing.
• Smart Cities: AI-powered urban planning, traffic management, and safety.

With its flexible, high-performance design, EYNTRY is set to revolutionize AI-powered vision technology in real-world environments.

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