Chatsistant has 2 types of Agents:User-facing: This Agent directly interacts with users conversationally in a Q&A fashion. Only a single user-facing Agent engages with the user when a new query is input into the chatbot.Background: This Agent never interacts with users directly and instead monitors the conversation in an ongoing fashion. All background Agents are run whenever the user submits a new query to the chatbot.Customizable Agents in Chatsistant
Chatsistant enables you to create powerful and adaptive workflows using two types of agents:1. Front-End User-Facing Agents
These agents directly interact with users conversationally in a Q&A format.
Only one user-facing agent engages with the user at a time when a new query is submitted.
They are designed to provide answers, complete tasks, or guide users through various interactions.
2. Background Agents (Built-In Functionality)
Background agents are now built-in to Chatsistant’s architecture, providing automated monitoring and task execution without requiring direct configuration. These agents work in the background to support front-facing agents by performing tasks such as:
Human Escalation: Automatically escalating conversations to a human agent based on user behavior or triggers.
Function Calling (Webhooks): Executing API calls to external systems when certain conversational conditions are met.
Conversational Tagging: Assigning dynamic tags to conversations to categorize user queries or detect specific intents (e.g., frustration detection).
Unlike front-facing agents, background agents are enabled and customized directly by users in the chatbot’s Customization Settings. They operate seamlessly behind the scenes to enhance chatbot functionality.Key Features of Built-In Background Agents
Trigger-Based Monitoring: Background agents automatically monitor user queries whenever a new message is submitted and execute actions such as tagging, escalation, or calling webhooks.
Workflow Optimization: By specializing in background monitoring, these agents create “multi-threaded” workflows, improving accuracy and consistency across chatbot interactions.
RAG Integration (Optional): In scenarios where background tasks need to evaluate user queries against policies, records, or other knowledge sources, RAG capabilities can be enabled.
How Built-In Background Agents Work
Simple, Focused Tasks: Background agents operate with predefined instructions. For instance, they monitor conversations for triggers like frustration, escalate to human support, or call a webhook when specific intents are detected.
No Manual Configuration Required: All agents created through Chatsistant are front-facing agents, while background capabilities are automatically enabled and integrated for seamless operation.
Optional Knowledge Source Access: Background agents can reference knowledge bases or RAG systems if needed for specific tasks, such as evaluating user statements before assigning tags or escalating queries.
Examples of Built-In Background Agent Use Cases
Human Escalation: Automatically escalate conversations to a human agent if a frustrated tone or critical issue is detected.
Function Calling: Execute specific actions, such as sending data to a CRM via webhook, based on user inputs like “Submit payment” or “Schedule appointment.”
Conversation Tagging: Dynamically tag conversations to streamline categorization. For example, add tags like “Frustrated” or “High-Priority” to enable tailored follow-ups.
By moving background agents to built-in functionality, Chatsistant ensures seamless integration into workflows, eliminating the need for manual setup while maintaining flexibility and scalability.A common use case for background Agents is conversation tagging. For an example of how to use background Agents to assign conversation tags, see Frustration Detection.
Here’s a fun setup that detects any mention of various fruits during the conversation and assigns the appropriate tags.