Quickstart

Build your first conversational AI voice agent in 5 minutes.

In this guide, you’ll learn how to create your first Conversational AI voice agent. This will serve as a foundation for building conversational workflows tailored to your business use cases.

Getting started

Conversational AI agents are managed through the ElevenLabs dashboard. This is used to:

  • Create and manage AI assistants
  • Configure voice settings and conversation parameters
  • Equip the agent with tools and a knowledge base
  • Review conversation analytics and transcripts
  • Manage API keys and integration settings

The web dashboard uses our Web SDK under the hood to handle real-time conversations.

Overview

In this guide, we’ll create a conversational support assistant capable of answering questions about your product, documentation, or service. This assistant can be embedded into your website or app to provide real-time support to your customers.

Conversational AI widget

The assistant at the bottom right corner of this page is capable of answering questions about ElevenLabs, navigating pages & taking you to external resources.

Prerequisites

Assistant setup

1

Sign in to ElevenLabs

Go to elevenlabs.io and sign in to your account.

2

Create a new assistant

In the ElevenLabs Dashboard, create a new assistant by entering a name and selecting the Blank template option.

Dashboard

Creating a new assistant
3

Configure the assistant behavior

Go to the Agent tab to configure the assistant’s behavior. Set the following:

1

First message

This is the first message the assistant will speak out loud when a user starts a conversation.

First message
Hi, this is Alexis from <company name> support. How can I help you today?
2

System prompt

This prompt guides the assistant’s behavior, tasks, and personality.

Customize the following example with your company details:

System prompt
You are a friendly and efficient virtual assistant for [Your Company Name]. Your role is to assist customers by answering questions about the company's products, services, and documentation. You should use the provided knowledge base to offer accurate and helpful responses.
Tasks:
- Answer Questions: Provide clear and concise answers based on the available information.
- Clarify Unclear Requests: Politely ask for more details if the customer's question is not clear.
Guidelines:
- Maintain a friendly and professional tone throughout the conversation.
- Be patient and attentive to the customer's needs.
- If unsure about any information, politely ask the customer to repeat or clarify.
- Avoid discussing topics unrelated to the company's products or services.
- Aim to provide concise answers. Limit responses to a couple of sentences and let the user guide you on where to provide more detail.
4

Add a knowledge base

Go to the Knowledge Base section to provide your assistant with context about your business.

This is where you can upload relevant documents & links to external resources:

  • Include documentation, FAQs, and other resources to help the assistant respond to customer inquiries.
  • Keep the knowledge base up-to-date to ensure the assistant provides accurate and current information.

Configure the voice

1

Select a voice

In the Voice tab, choose a voice that best matches your assistant from the voice library:

Voice settings

Using higher quality voices, models, and LLMs may increase response time. For an optimal customer experience, balance quality and latency based on your assistant’s expected use case.
2

Testing your assistant

Press the Test AI agent button and try conversing with your assistant.

Analyze and collect conversation data

Configure evaluation criteria and data collection to analyze conversations and improve your assistant’s performance.

1

Configure evaluation criteria

Navigate to the Analysis tab in your assistant’s settings to define custom criteria for evaluating conversations.

Analysis settings

Every conversation transcript is passed to the LLM to verify if specific goals were met. Results will either be success, failure, or unknown, along with a rationale explaining the chosen result.

Let’s add an evaluation criteria with the name solved_user_inquiry:

Prompt
The assistant was able to answer all of the queries or redirect them to a relevant support channel.
Success Criteria:
- All user queries were answered satisfactorily.
- The user was redirected to a relevant support channel if needed.
2

Configure data collection

In the Data Collection section, configure details to be extracted from each conversation.

Click Add item and configure the following:

  1. Data type: Select “string”
  2. Identifier: Enter a unique identifier for this data point: user_question
  3. Description: Provide detailed instructions for the LLM about how to extract the specific data from the transcript:
Prompt
Extract the user's questions & inquiries from the conversation.
Test your assistant by posing as a customer. Ask questions, evaluate its responses, and tweak the prompts until you’re happy with how it performs.
3

View conversation history

View evaluation results and collected data for each conversation in the Call history tab.

Conversation history

Regularly review conversation history to identify common issues and patterns.

Your assistant is now configured. Embed the widget on your website to start providing real-time support to your customers.

Next steps

Customize your agent

Learn how to customize your agent with tools, knowledge bases, dynamic variables and overrides.

Integration quickstart

Learn how to integrate Conversational AI into your app using the SDK for advanced configuration.

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