Autonomous Email Management System Using Rule-Based Heuristic Learning for Intelligent Classification and Response Automation

This paper presents an Autonomous Email Management System designed to automate email classification, prioritization, and response generation using a rule-based heuristic engine. The system analyzes incoming emails based on intent, tone, and priority, and performs intelligent actions such as spam filtering, meeting scheduling, reminder creation, and adaptive reply generation without relying on external AI APIs or large language models. Built using Node.js, PostgreSQL, Gmail API, and OAuth 2.0 authentication, the proposed solution provides a deterministic, auditable, and cost-effective alternative for structured email automation tasks. Experimental evaluation demonstrates effective routing across multiple email categories including meeting requests, task requests, questions, personal messages, spam, and informational emails. Keywords: Email Automation, Rule-Based System, Gmail API, Intent Classification, Smart Reply, Autonomous Agent.