Agentic conversations in Virtual Agent
Summarize
Summary of Agentic Conversations in Virtual Agent
The Virtual Agent enables users to engage in agentic conversations, where the system can understand and execute complex queries by reasoning and planning across various AI agents, skills, and resources. This allows for efficient handling of user requests by utilizing existing capabilities within the system, ensuring tasks and subtasks are completed effectively.
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Key Features
- Dynamic Task Management: The system identifies and utilizes specific agents to perform tasks. If none are available, the Search Agent is employed to find relevant skills or answers.
- Execution of Skills: When needed, the system automatically executes discovered skills to complete user requests.
- Orchestration: Capable of planning and orchestrating execution among multiple agents and skills for complex tasks.
- AI Agent Configuration: Requires admin role to create and configure assistants, assign them to portals, and ensure proper skills are integrated.
Key Outcomes
By leveraging agentic conversations, users can expect:
- Improved response accuracy through tailored answers to multiple questions or requests.
- Streamlined execution of complex tasks, allowing for sequential processing of multiple actions based on user input.
- Enhanced user experience as the system understands intents and fulfills them effectively, even when combining different types of queries and actions.
When you ask a question to the virtual agent, the agent understands the query. It can reason, plan, and execute across AI agents, virtual agent topics, conversational actions and subflows, catalogs, KB articles, custom skills, and any Now Assist in Virtual Agent supported skills to help you.
- If for the given assistant, specific agents are available to perform user tasks or sub tasks, they’re used.
- If a specific agent isn’t available for the task or sub task, the system automatically employs the Search Agent to discover answers or appropriate skills within the system (again based on the assistant scope).
- If skill execution is required, the system automatically executes the discovered skills.
- The system can plan and orchestrate execution among multiple agents, skills, and QnA to accomplish complex tasks.
Enable AI agents in Virtual Agent
Role required: admin or virtual_agent_admin
- Create and configure multiple assistants with specific scope and map the assistants to one or more portals.The configuration consists of the following:
- Creating an assistant in Virtual Agent or using the default. To create an assistant, see Create an assistant
- Assigning specific assistants to a specific portal or portals. For more information, see Display your assistant on a portal or channel.
- Ensure that the AI agents skill is added to the assistant.
- Map or publish an agent to one or more assistants on AI Agent Studio to make the agent available within a specific assistant. For more information, see Create an AI agent.
During execution, only the configured AI agents are considered for the current assistant and dynamically makes them available to the Orchestrator for planning.
Examples of AI agent behavior for user utterances
| Agents | Skills/Topics | KB Articles |
|---|---|---|
|
Check IT Ticket status agent Email Agent Meeting scheduling Agent |
Order coffee Order food Order laptop Order accessories |
Spam ESPP policy |
Scenario 1: Multiple questions from KB articles
Utterance: How do I avoid spam? How do I detect it?
- Non-agentic response: Produces a single mixed answer.
- Agentic response: Breaks it into two questions and provides a better answer for each one of them.
Scenario 2: Multiple skills with slot filling
Utterance: Hey, order a coffee for me, preferably dark roast and something to eat, maybe a pizza?
- Non-agentic response: Produces a single answer. Mostly listing all matching available skills. No auto-execution since it matched multiple skills.
- Agentic response: Breaks it into two distinct tasks, order coffee and order food/pizza. Executes one after another, completing the entire user request.
Scenario 3: Complex utterance with a combination of skills, agents, and QnA
Utterance: I am going on PTO tomorrow. Get my expense report and my IT ticket status. Send a summary of the expense report to John Jacob and the details on ticket status to Robert Williams, informing them of my PTO and requesting them to work on them.
- Non-agentic response: Produces a single answer. It lists all matching available skills. No auto-execution will take place since it matched multiple skills.
- Agentic response: Breaks it into multiple distinct tasks, reasons and plans, understands the dependencies, and executes one after another, completing the entire user request using output from prior actions as context as needed.
Scenario 4: Complex utterance with a combination of QnA (KB) and agent
Utterance: What is the maximum contribution amount for espp? Send an email to Robert with the details.
- Non-agentic response: Produces a single answer and doesn’t complete or even suggest the second action since there’s no corresponding skill.
- Agentic response: Understands the two separate intents and executes them in sequence while using the output from the first intent to fulfill the second intent.