Scope

Objective

EYNTRY’s AI & Data Science scope focuses on developing efficient, scalable, and high-performance AI models for real-time vision processing, ensuring accuracy and reliability.

Core Responsibilities

• Model Development: Implement YOLOv8 for real-time object detection.
• Data Pipeline Management: Stream AI events using Kafka and MQTT.
• Optimization & Benchmarking: Enhance model performance with TensorRT and evaluate using TorchBench.
• Scalability & Deployment: Support both cloud-based and edge AI inference.

Design Considerations

• Efficiency: Minimize latency for real-time AI detection.
• Resource Optimization: Balance computational load across cloud and edge devices.
• Data Privacy: Ensure secure data handling for AI model training.

Expected Outcomes

• High-accuracy AI models optimized for real-time performance.
• Efficient data streaming and processing pipelines.
• Scalable AI deployment across multiple environments.

This scope ensures that EYNTRY’s AI-driven vision capabilities remain cutting-edge, robust, and aligned with evolving technological advancements.