Manual processes, delays, and siloed information hinder efficient customs clearance, posing challenges to trade facilitation, compliance, and security. Effectively identifying high-risk shipments and sharing critical information across relevant government agencies like Bureu of Standards, Ministry of Health, and Police is a significant hurdle.Zimulikizi is an AI-powered multi-agent system designed to automate and intelligentize this process. It acts as a smart layer within customs import operations. The system is built with a multi-agent architecture where different agents specialize in key tasks.It begins by ingesting raw import data and associated documents (like invoices, permits, manifests) from sources akin to the Tax system. This data is then processed by agents leveraging advanced AI/ML models. Vision AI is used for document analysis, takes tasks like Optical Character Recognition (OCR), identifying and verifying stamps or seals, and extracting data from document images. Natural Language Processing (NLP) agents extract structured information from text fields and descriptions. Machine Learning models analyze the consolidated data to calculate a sophisticated risk score for each consignment and detect anomalies that might indicate non-compliance or security threats.Based on this comprehensive AI-driven analysis, an intelligent Routing Agent automatically determines which specific government agencies have a regulatory interest in that particular shipment. It then prepares and dispatches tailored information packets – containing only the data relevant to that agency's mandate e.g,health-related details of Health Dep, standards compliance info for BS, risk and importer data for Police).Automated processing delivers: accelerated low-risk shipment clearance high-risk inspections; real-time agency coordination . detection of misdeclarations, undervaluation, prohibited goods; and prevention of dangerous/illegal imports—enhancing efficiency, compliance, and security.