This AI based project focuses on remote monitoring of vessel telemetry. This innovative system continuously collects and analyses real-time telemetry data from various sensors installed on the vessel. The data includes critical parameters such as engine performance, fuel consumption, navigation status, and environmental conditions. Data is processed using advanced AI algorithms. These algorithms are designed to detect anomalies and identify potential issues before they escalate. If any error codes are raised on the ship, the system automatically researches and identifies the root cause of the problem. The AI system leverages a comprehensive database of known issues and solutions, ensuring that the error codes are accurately diagnosed. Upon identifying the error, the AI system proposes the next best action to the operator. This recommendation is based on historical data, expert knowledge, and real-time analysis. The proposed actions could range from simple troubleshooting steps to more complex maintenance procedures. By providing these actionable insights, the AI system helps operators make informed decisions quickly, minimising downtime and enhancing the overall safety and efficiency of the vessel. The remote monitoring capability allows fleet managers and operators to oversee multiple vessels from a centralised location. This not only improves operational efficiency but also ensures that any issues are addressed promptly, regardless of the vessel's location. The integration of AI in monitoring and diagnostics significantly reduces the risk of human error, leading to more reliable and efficient maritime operations. Overall, this AI project represents a significant advancement in maritime technology, offering a robust solution for real-time monitoring, automated diagnostics, and proactive maintenance of vessels.