Overview
An AI Agent combines natural-language understanding, voice synthesis, and workflow automation. Each agent is fully configurable through four main tabs inside the Studio:- Voice & Guidelines – Define how the agent greets callers, which voice it uses, and the system guidelines that steer its behaviour.
- Knowledge Base – Grant the agent access to company knowledge at runtime.
- Actions – Orchestrate API calls before, during, and after a call so the agent can fetch data, carry out tasks, and hand off results.
- Settings – Fine-tune transcription with custom keywords and other preferences.
1 · Voice & Guidelines Tab
| Configuration | Why it matters |
|---|---|
| Name | Clear, descriptive names make it easy to identify the agent in dashboards and analytics. |
| Initial Message | The very first sentence your agent says on answering the phone. You can include variables (e.g. {{firstName}}) extracted from Pre-Call Actions. |
| TTS Voice | Choose any text-to-speech voice that match your brand personality. |
| Guidelines | System-level instructions written in markdown. Set the agent’s role, tone, and constraints. Use variables to reference data fetched in Pre-Call Actions. |
2 · Knowledge Base Tab
Link zero or at most 2 Knowledge Groups that the agent can search during a call to answer user’s queries. The AI automatically retrieves relevant passages at runtime, enabling precise, up-to-date responses without hard-coding content in prompts.An AI Agent can only be linked to at most two Knowledge Groups
3 · Actions Tab
Actions let the agent talk to your backend systems via HTTPS. They come in three flavours:3.1 · Pre-Call Actions
- Runs before the agent speaks.
- Common use-case: FetchContact – pull CRM details and store them in variables like
{{firstName}},{{accountStatus}}. - Variables created here are available to personalize Initial Message and Guidelines.
- Variables values are available throughout the lifetime of the interaction and can be utilized in During Call or Post Call Actions.
You can configure multiple Pre-Call Actions which will be executed sequentially in the order they were created. This allows you to chain API calls and build up context before the conversation starts.
Only variables extracted from Pre-Call Actions can be used to personalize the Initial Message and Guidelines. No other variable values are available at this stage.
3.2 · During-Call Actions
- Triggered on demand when the caller asks for something (e.g. “CheckOrderStatus”).
- Provide comprehensive documentation for each action, including specific trigger conditions and use cases. Detailed context helps the AI model accurately determine when and how to execute the action.
- Define parameters to specify the data requirements for action execution. Each parameter can be configured with:
- Name
- Description (use this to provide format requirements and context to help the AI collect data correctly)
- Type (String, Number and List)
- Required/Optional flag Parameters are optional and you can configure zero or more as needed for the action.
- You can define filler messages that the agent speaks while waiting for the API response using the Say node in the flow builder
- External API calls can be executed through the flow’s API Request Node
During-Call Action names must only contain letters, numbers, underscores or hyphens, and be between 1-63 characters long (e.g. use
check_order_status or CheckOrderStatus, not Check Order Status!)3.3 · Post-Call Actions
Executed when the conversation ends—whether the caller hangs up, self-serves successfully, or escalates to a human. Typical tasks include:- Generating a call summary and disposition
- Saving the transcript to your CRM or data warehouse
- Kicking off downstream workflows (e.g. ticket creation)
4 · Settings Tab
Use this tab to enhance speech-to-text accuracy:- Transcription Keywords – Add product names, acronyms, or industry-specific terms (e.g. medical jargon) that the transcription engine might otherwise miss.
Best Practices
- Start simple. Launch with a lightweight set of actions and expand iteratively.
- Keep guidelines concise. The shorter the system prompt, the faster the agent responds.
- Monitor analytics. Use the built-in dashboard to track resolution rates, average call duration, and customer sentiment.
- Iterate on feedback. Real-world conversations reveal edge cases you can cover with new actions or guideline tweaks.