This document is a basic guide to Agent Assist resources. More details about the resources described below can be found in the reference documentation. We recommend that you familiarize yourself with this guide before diving into Agent Assist.
A Conversation is a resource that represents an exchange between two or more participants. Every time a conversation participant's utterance is passed to Agent Assist as part of a Conversation resource, a message is created and stored for the conversation.
Each conversation is created using a conversation profile. Each conversation profile contains a set of parameters that control the suggestions provided to the human agent during a conversation. You can also configure a conversation profile for use with a virtual agent, which auto-generates a reply to the end-user.
You can create a conversation profile either by using the Agent Assist Console or by calling the API directly.
Each conversation can have the following participants:
END_USER: Participant is an end-user. This is the person the agent is conversing with.
AUTOMATED_AGENT: Participant is an automated agent.
HUMAN_AGENT: Participant is a human agent.
Dialogflow agents are virtual agents that you can build and configure for conversations with your end-users. You can design your system so that end-users initially interact with a virtual agent before being escalated to a human agent. You can use either a Dialogflow ES or Dialogflow CX agent.
A conversation with an end-user has multiple stages:
- Connection stage: The end-user initiates a chat dialog.
- Virtual agent stage: The end-user is connected to a Dialogflow virtual agent. The virtual agent communicates with the end-user and attempts to resolve all issues and requests. You can set up your system to bypass the virtual agent and handoff stages.
- Handoff stage: If the virtual agent cannot resolve all end-user issues, the conversation is handed off to a human agent.
- Agent Assist stage: The end-user is connected to one or more human agents. Agent Assist supplies real-time document and response suggestions to the human agent that are relevant to the conversation.
- Termination stage: The end-user is disconnected from the text chat.
To implement Agent Assist for text-based conversations you must integrate the Agent Assist API into your agent desktop.