Scope

Objective

The backend of EYNTRY serves as the foundation for AI-driven vision processing, ensuring scalability, security, and real-time performance. It is designed to efficiently handle authentication, AI inference, event processing, data storage, and monitoring.

Core Responsibilities

• API Management: Expose structured REST and GraphQL endpoints for seamless client interaction.
• Authentication & Security: Implement robust authentication (OAuth2, JWT) and role-based access control.
• AI Processing: Execute real-time AI inference using YOLOv8 and TensorRT.
• Event Handling: Stream AI and user-generated events via Kafka and MQTT for real-time automation.
• Data Storage: Manage structured data (PostgreSQL) and unstructured assets (MinIO for object storage).
• Logging & Monitoring: Ensure observability with Prometheus and Grafana, tracking system health and performance.

Design Considerations

• Scalability: The system must handle increasing loads, ensuring minimal latency.
• Microservices Architecture: Each core function operates independently, allowing modular upgrades.
• Cloud & Edge Compatibility: Services must function seamlessly across cloud environments and edge devices.

Expected Outcomes

• A robust, secure, and scalable backend infrastructure.
• Real-time AI processing with optimized response times.
• Efficient data handling for both structured and unstructured content.
• A comprehensive monitoring and logging system to ensure reliability.

This scope outlines the backend’s critical role in powering EYNTRY’s AI-driven vision platform, ensuring a seamless and efficient architecture.