Hybrid Intelligent Archival Method for Customer Communication Management

Abstract In today’s digital era, the exponential growth in customer communication data necessitates archival systems that are scalable, secure, and compliant with evolving regulatory standards. In this paper, I propose a novel hybrid intelligent archival method that integrates cloud and edge storage infrastructures with AI-driven data curation and blockchain-enabled compliance. Unlike traditional archival approaches that rely on isolated technologies, my method combines these techniques into a unified framework that dynamically adapts to workload fluctuations, optimizes data retrieval, and enforces data retention policies via smart contracts. The paper details the system architecture, describes the underlying algorithms, and presents a theoretical evaluation using simulation models and performance metrics. The proposed method promises significant improvements in storage efficiency, data integrity, and operational compliance for managing customer communication data. Index Terms Archival Systems, Cloud Storage, Edge Computing, Blockchain, Artificial Intelligence, Data Curation, Compliance, Hybrid Architecture, Digital Transformation.