Quickstart

Create an account, build your first agent, and deploy it in minutes.

Create an account, build an agent, add knowledge, test it, and deploy – in five steps.

Prerequisites

• A use case in mind (e.g., customer support, reservations, FAQ)

1. Create your account (~1 min)

   Go to the sign-up page and create your PolyAI account.

   Google SSO

   1. Click “Sign up with Google”

   2. Select your Google account or enter your credentials

   3. Click “Continue” to authorize PolyAI

      

   Email and password

   1. Enter your first name, last name, and email address

   2. Create a password (at least 12 characters, with 3 of 4 character types: lowercase, uppercase, numbers, special characters)

   3. Click “Create account” and verify your email

      

   Once signed in, you’ll land on the Agent Studio home page.

2. Create your agent (~2 min)

   From the home page, click + Agent to start the agent creation wizard. You can create a blank agent or import an existing configuration.

   Configure the basics:

   • Agent name – internal identifier for your project
   • Response language – primary language for responses (see multilingual support for additional languages)
   • Voice – select from available text-to-speech (TTS) voices
   • Welcome greeting – first message users receive (can be customized later in agent settings)

   Click Next to enter Agent Studio.

   

   You can also duplicate an existing agent by clicking the three-dot menu next to any agent on the home page.

3. Add knowledge (~5 min)

   Navigate to Build > Knowledge > Managed Topics in the sidebar.

   Click Add topic and provide:

   • Topic name – what this topic covers (e.g., “Store hours”)
   • Sample questions – up to 20 ways users might ask (e.g., “When are you open?”)
   • Answer – the response your agent should give

   Click Save to create the topic.

   

   Changes are saved as Drafts. Publish to Sandbox to test them. Learn more about environments and versions.

   Optional: Add more topics to expand your agent’s capabilities. You can also:

   • Upload PDFs or URLs to auto-generate topics
   • Connect external knowledge sources like Zendesk or Google Sheets using the Connected tab in Knowledge
   • Add actions to trigger handoffs, SMS, or other behaviors

   See the full Managed Topics guide for details on how RAG (retrieval-augmented generation) powers topic matching.

4. Test your agent (~2 min)

   In-browser call

   The fastest way to test – uses your device’s microphone directly.

   1. Click the phone icon in the top-right corner

   2. Select Sandbox from the environment dropdown

   3. Begin speaking to your agent

      

   Webchat

   Test with text-based chat, directly from Agent Studio.

   1. Go to the agent main page
   2. Click the webchat icon to open a text-based conversation

   The chat window shows tool calls and topic citations alongside the conversation. Click the Settings icon to toggle these.

   

   See webchat setup for more details.

   Phone

   Test in a production-like environment by calling a connected number.

   1. Go to Configure > Numbers in the sidebar
   2. Click “Add number” to purchase a number or connect an existing one
   3. Call the number to speak with your agent

   See Numbers for setup instructions.

   Testing tips:

   • Use specific keywords to trigger your agent’s topics
   • Test with different accents and speaking styles
   • For multilingual agents, switch languages mid-conversation to test detection
   • Review conversations in the Conversations dashboard after testing
5. Deploy to production (~1 min)

   Promote your agent through the deployment pipeline:

   1. Go to Deployments > Environments in the sidebar
   2. Click Promote to Pre-release for user acceptance testing (if available in your project)
   3. Click Promote to Live to make your agent production-ready

   Each environment can have its own phone number and configuration.

   

   Some projects use a simplified pipeline that promotes directly from Sandbox to Live, skipping Pre-release. You can roll back to any previous version if issues arise – see the deployment pipeline guide for details.

Next steps

Add advanced features

Connect APIs and add dynamic behavior with Python functions

Build conversation flows

Multi-step workflows for bookings, forms, and structured tasks

Configure voice settings

TTS, voice selection, and audio settings

Monitor performance

Dashboards, conversation review, and metrics

How your agent works

Each conversation turn follows a pipeline: ASR (speech to text) → LLM (knowledge retrieval and response generation) → TTS (text to speech). See architecture for a detailed breakdown, or processing order for the step-by-step flow.