A blockchain-empowered AutoML reputation system for anonymous customer service in SMEs.

A typical manual customer service model for small and medium-sized enterprises (SMEs) is transitioning to automated customer service, using various computing resources to deliver more effective and high-quality services. The prerequisites for automated customer service include extensive data and strong data analytics capabilities. Unfortunately, because of their small size and lack of resources, many SMEs, particularly small and medium-sized companies, lack adequate data and ability. SMEs are forced to rely on external computing sources, which prevents them from developing core competencies in customer service. To address this issue, we propose a blockchain-enabled and automated machine learning (AutoML) model that uses decentralized datasets for customer services. Blockchain, a secure and transparent digital ledger, ensures the integrity and traceability of data, making it an ideal solution for storing and managing customer service data. Blockchain smart contracts allow customer services to be carried out automatically in a pipeline, producing review scoring reputation systems. The proposed scheme includes the following: model implementation, enterprise registration, review aggregation, verification, and review evaluation integrated into blockchain. To guarantee that the customer service system is traceable and that the data of each reviewing enterprise is safely, effectively, and impenetrably stored on the blockchain nodes, we first present a mechanism for review data administration and storage utilizing blockchain. Next, we provide a pipeline that efficiently integrates the crucial processes of model creation, review collection, verification, and model assessment using an AutoML model. The experimental findings show that our proposed system reliably and effectively assesses customer service in SMEs.