Cisco employs a 'supervisor approach' to decompose complex customer queries across specialized AI agents, improving response quality.

Our multi-agent system starts with a supervisor agent that orchestrates tasks, understands user intentions, and delegates to specialized sub-agents, ensuring high accuracy and reliability.

The agent personalizes answers based on user roles, providing detailed responses for due diligence specialists and general answers for advisors.

An agent is something a human can delegate tasks to, and we're aiming for agents to handle more complex tasks over time.

AI agents can help product managers offload draining tasks, allowing them to focus on customer immersion, data analysis, and strategic thinking.

We're creating a better, more human-like customer support experience with AI agents to help users get the support they need efficiently.

Our routing product allows customers to dynamically define criteria for directing conversations to human agents, while our agent assist product acts as a co-pilot for human support agents, enhancing their efficiency by providing AI-driven insights.

AI models have become proficient at processing unstructured data, allowing them to generate helpful responses and take actions in customer support scenarios.

For complex queries, we employ text-to-code generation capabilities with human supervision to ensure accurate execution of tasks.