Multi Agent Solutions

Agentic AI systems are designed to perform specific tasks autonomously by simulating human-like decision-making processes. In the context of a hackathon focused on service due reminders, these systems can be structured using a multi-agent architecture, where each agent is responsible for a distinct aspect of the service reminder process. Here's a brief overview of the agents you mentioned: 1. Vehicle Telemetry Tracker Agent: This agent monitors vehicle telemetry data to identify vehicles that have reached a specified threshold, such as a certain number of kilometers driven. It autonomously processes data to generate alerts or reports, ensuring timely service reminders. Customer Interaction Specialist Agent: This agent engages with customers to gather necessary details for scheduling service appointments. It collects preferences such as preferred locations, dates, and times, ensuring that customer needs are met efficiently. Dealer Engagement Specialist Agent: This agent communicates with dealers to confirm the availability of service slots based on customer preferences. It ensures that the service appointments can be scheduled without conflicts, facilitating a smooth service process. In your hackathon setup, these agents interact with simulated APIs that mimic the behavior of real-world customers, tables, and dealers. This allows for testing and demonstrating the effectiveness of the multi-agent system in managing service due reminders, showcasing how AI can streamline and automate complex processes in a service-oriented environment.