# Agent configuration

In order to set up your agent, create a new workspace and click on the Agents tab. You will then be able to choose an agent template from the agent store.

Give your agent a name, and give it a description - this is for your internal reference. \
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Then click on configure. Here you will be able to personalise the agent to your brand, business and tone.<br>

#### Business name

The name of your business as it will be referenced by the AI agent during conversations. This ensures the agent identifies itself correctly and represents your brand consistently across all customer interactions.

#### Product name

Defines the product or service category the AI agent is supporting. This helps the agent contextualise its responses and stay relevant to your specific offering when answering customer queries.

#### Tone

Sets the overall conversational style the agent uses when responding. Options like "Formal" produce professional, polished language, while more casual settings create a friendlier, conversational feel better suited to informal channels.

#### Language variant

Selects the language the AI agent will use when communicating with customers. Choose the variant that matches your customer base to ensure responses feel natural and locally appropriate.

#### Temperature

Controls how creative or predictable the AI agent's responses are. Lower values (e.g. 0.30) produce more consistent, focused answers, while higher values introduce more variation — keep this low for customer support where accuracy and reliability matter most.

#### Model

Specifies which underlying AI model powers the agent's responses. Different models offer different trade-offs between speed, cost, and capability, so choose the one that best fits your performance and budget requirements.

#### UI formatting style

Controls how the AI agent formats its responses. Choose "Markdown" for rich formatting with bold text, bullet points, and links, or "Plain Text" for simple, unformatted replies suited to channels where Markdown isn't supported.

#### Empathy level

Adjusts how emotionally attuned the agent's tone is when responding to customers. Set to "High" for warm, understanding language that acknowledges the customer's situation, or lower it for a more matter-of-fact, efficient style.

#### Max sentences

Sets the maximum number of sentences the AI agent will use in a single reply. Keep this low for concise, chat-style responses, or increase it when your use case requires more detailed explanations.

#### Technical level

Controls how much technical detail and terminology the agent includes in its responses. "High" suits audiences comfortable with domain-specific language, while lower settings produce simpler, more accessible explanations.

#### Support team reference

Defines the name or label the AI agent uses when referring to your human support team. For example, entering "our Customer Care team" means the agent will use that phrase when offering to escalate or hand over a conversation.

You can then save the configuration for your agent, and proceed to test its responses in the playground.

You can also create multiple configurations in order to compare which combination of settings provides the most suitable answers for your use case.\
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Then activate the agent and all new inbound customer conversations will be handled by your new AI agent.\
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It's also possible to deactivate the agent via the configure tab at any time, this will turn the agent off and customer messages will no longer be responded to by the AI agent.

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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://converso.gitbook.io/product-documentation/ai-agents/agent-configuration.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.