> ## Documentation Index
> Fetch the complete documentation index at: https://docs.ansa.so/llms.txt
> Use this file to discover all available pages before exploring further.

# Customer Support

> Build an AI-powered support agent that answers questions from your help docs, escalates complex issues, and learns from human responses.

export const Screenshot = ({src, alt}) => <img src={src} alt={alt} className="rounded-lg border border-gray-200" />;

## Overview

Ansa is ideal for customer support teams who want to:

* Deflect repetitive questions with instant, accurate answers
* Escalate complex issues to human agents seamlessly
* Build a growing knowledge base from real support interactions
* Provide 24/7 support without scaling headcount

<Screenshot src="/screenshots/chat.png" alt="Customer support chat" />

## Recommended Configuration

### 1. Knowledge Base Setup

Index your existing help documentation to give your agent comprehensive knowledge:

**Recommended sources:**

* Help center articles (web crawl or upload)
* FAQ documents
* Product documentation
* Troubleshooting guides

<Screenshot src="/screenshots/web-sources.png" alt="Web sources configuration" />

<Tip>
  Use the **auto-detect feature** during onboarding to automatically discover and index your help pages. Ansa will probe common paths like `/help`, `/support`, `/faq`, and `/docs`.
</Tip>

### 2. Agent Settings

| Setting           | Recommended Value                              | Why                                                      |
| ----------------- | ---------------------------------------------- | -------------------------------------------------------- |
| **Model**         | Claude 3.5 Sonnet or GPT-4o                    | Best balance of accuracy and speed                       |
| **Temperature**   | 0.3 - 0.5                                      | Lower temperature for more consistent, factual responses |
| **System Prompt** | Include tone, escalation rules, and boundaries | See example below                                        |

**Example System Prompt:**

```
You are a helpful customer support agent for [Company Name].

Your role:
- Answer questions accurately based on the knowledge base
- Be friendly, professional, and concise
- If you don't know the answer, say so honestly
- For billing issues, account access, or complex technical problems, offer to connect the user with a human agent

Never:
- Make up information not in the knowledge base
- Share internal processes or confidential information
- Make promises about refunds or credits without escalating
```

### 3. Escalation with Confidence Thresholds

Use confidence scores to automatically escalate low-confidence responses:

<Screenshot src="/screenshots/analytics.png" alt="Analytics showing confidence scores" />

| Confidence Level    | Action                                    |
| ------------------- | ----------------------------------------- |
| **High (80%+)**     | Respond automatically                     |
| **Medium (50–79%)** | Respond but offer human escalation        |
| **Low (below 50%)** | Show contact form or escalate immediately |

### 4. Escalation Form Tool

Create a form tool for human escalation:

```json theme={null}
{
  "name": "contact_support",
  "description": "Use this when the user needs human assistance, has a billing issue, or when you cannot answer their question confidently.",
  "executionType": "form",
  "formSchema": {
    "fields": [
      { "name": "email", "label": "Email", "type": "email", "validation": { "required": { "value": true, "message": "Email is required" } } },
      { "name": "issue", "label": "Describe your issue", "type": "textarea" }
    ],
    "submitLabel": "Contact Support",
    "successMessage": "We've received your request. A support agent will reach out within 24 hours."
  },
  "formPostActions": [
    { "type": "email", "recipientIds": ["support-team-user-id"], "subject": "Support Escalation" },
    { "type": "slack", "webhookUrl": "https://hooks.slack.com/...", "messageTemplate": "🚨 New escalation from {{email}}: {{issue}}" }
  ]
}
```

### 5. Widget Triggers

Set up proactive engagement to help users before they get frustrated:

| Trigger                  | When                                  | Action                                        |
| ------------------------ | ------------------------------------- | --------------------------------------------- |
| **Time on support page** | 30 seconds on `/help/*`               | Open chat with "Need help finding something?" |
| **Scroll depth**         | 75% scroll on troubleshooting article | Show bubble "Still having issues?"            |
| **Exit intent**          | About to leave support page           | Show form for feedback                        |

<Screenshot src="/screenshots/widget.png" alt="Widget builder" />

## Email Channel for Async Support

Enable the email channel to handle support emails with AI:

1. Forward support emails to your agent's inbound address
2. Set confidence threshold (recommended: 70%)
3. Configure low-confidence action to "forward" to human reviewers
4. Enable **Auto Learn** to automatically create Q\&A entries from human responses

<Screenshot src="/screenshots/integrations-email.png" alt="Email channel settings" />

## Monitoring & Improvement

### Review Conversation History

Regularly review conversations to identify:

* Common questions that need better documentation
* Low-confidence responses that need knowledge base updates
* Patterns in escalated issues

<Screenshot src="/screenshots/history.png" alt="Conversation history" />

### Track Key Metrics

Monitor these analytics:

* **Average confidence score** — Target 75%+
* **Escalation rate** — Track form submissions vs. resolved chats
* **Response quality** — Review feedback ratings

## See Also

* [Confidence Scores](/user-guides/confidence-scores) — Understanding confidence levels
* [Triggers](/widget/triggers) — Setting up proactive engagement
* [Form Tools](/tools/form-tools) — Creating escalation forms
* [Email Channel](/integrations/email) — Handling email support with AI
* [Conversation History](/user-guides/history) — Reviewing and improving responses