Abstract: This paper presents a self-designed AI-powered titration system that automates conventional titration processes through image recognition technology. Using the titration of calcium ions (Ca²⁺) with ethylenediaminetetraacetic acid disodium salt (EDTA) as a case study under pH conditions of pH = 12-13, the system employs a high-definition camera to capture solution color changes. Integrated with deep learning algorithms, it enables real-time monitoring of titration progress and endpoint determination. Compared to traditional manual titration, the AI-enhanced system not only enhances precision and efficiency but also utilizes a photonic sensor for precise drop counting and real-time titration rate adjustment. Experimental results demonstrate that the optimized AI system achieves high accuracy in both titration volume and concentration determination, significantly minimizing human error while exhibiting robust automation capabilities. This system offers effective technological support for advancing the intelligence and automation of chemical experiments, with promising potential for widespread application in educational and industrial settings.