Authors: Abhinay Gour, Prof. Geeta Santosh
Abstract: In the evolving landscape of digital communication, ensuring the authenticity and reliability of email addresses and domains is critical for maintaining security, optimizing deliverability, and mitigating fraud. This paper presents an integrated architecture for an AI-driven email verification and domain intelligence system, combining real-time validation, domain reputation assessment, and a dynamic risk scoring engine. The proposed system leverages machine learning algorithms to detect syntactic anomalies, validate domain existence, and assess historical engagement patterns, while incorporating threat intelligence to evaluate potential risks such as phishing, spam, and disposable addresses. By unifying these components, the architecture not only enhances email deliverability but also provides actionable insights for cybersecurity and marketing strategies. Experimental results demonstrate that the AI-enhanced approach significantly outperforms traditional rule-based verification methods in accuracy, response time, and risk detection, offering a scalable solution for organizations requiring robust email and domain trustworthiness assessment.
