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

# Email settings

> Learn how email assignment and auto-send threshold work, and when your AI agent drafts, auto-sends, or escalates for human review.

## Overview

The **Email** settings page controls how your agent handles inbound email conversations for your workspace.

For most teams, the two most important settings are:

1. **Assignment** (which agent is in charge of responding to emails)
2. **Auto-send threshold** (how confident the agent must be before sending automatically)

***

## How email assignment works

<Frame>
  <img src="https://mintcdn.com/weav-a01be0f7/reJWL8GwUmMMtmdB/images/assignment.png?fit=max&auto=format&n=reJWL8GwUmMMtmdB&q=85&s=3b66d3f4838ee85f6111d961b597e290" alt="Assignment" width="1304" height="180" data-path="images/assignment.png" />
</Frame>

### What “Assignment” does

When you click **Assign to email** on an agent:

* That agent becomes the workspace’s **active email agent**
* Any previously assigned email agent is automatically unassigned
* Only **one** agent can be assigned to email at a time

<Info>
  Think of this as selecting your workspace’s “primary AI email teammate.”
</Info>

### What happens to conversations after assignment

Assignment mainly affects **new inbound email conversations** and conversations that don’t already have an agent attached.

For incoming email conversations, Weav assigns the active email agent to the conversation

### Important nuance (where confusion usually happens)

Changing assignment does **not** mass-migrate every existing conversation automatically.

So if a conversation is already assigned elsewhere, that existing assignment will stay as-is until reassigned by your team.

***

## How auto-send threshold works

This setting decides whether the AI response should be:

* escalated (no AI reply sent),
* saved as a draft for human user review,
* or auto-sent reply.

### The mental model (simple version)

For each eligible customer email:

1. The AI generates a draft and confidence score
2. Weav compares confidence against routing thresholds
3. Weav chooses one path: **escalate**, **draft**, or **auto-send**

***

## Confidence levels in the UI

Your slider options map to stricter or looser auto-send behavior.

<Frame>
  <img src="https://mintcdn.com/weav-a01be0f7/reJWL8GwUmMMtmdB/images/confidence.png?fit=max&auto=format&n=reJWL8GwUmMMtmdB&q=85&s=db389650c81a09a06332c7983fab4ec5" alt="Confidence" width="1992" height="334" data-path="images/confidence.png" />
</Frame>

| Setting              | Meaning                 | Effect                                          |
| -------------------- | ----------------------- | ----------------------------------------------- |
| Low confidence       | Lower bar for auto-send | More replies auto-send; fewer drafts            |
| Medium confidence    | Balanced bar            | Mix of auto-sent and reviewed drafts            |
| High confidence      | Conservative default    | Only stronger replies auto-send                 |
| Very high confidence | Strictest bar           | Most replies become drafts                      |
| Never auto-send      | Auto-send is disabled   | AI can prepare drafts, but will never auto-send |

***

## Exactly when each outcome happens

### 1) AI does **not** auto-respond (human path / escalation)

This happens when confidence is too low (below the safety floor) or escalation conditions are met.

Typical result:

* Conversation is routed toward a human
* AI draft is not used as the final response path

### 2) AI creates a **draft for review**

This happens when confidence is acceptable but not high enough for auto-send.

Typical result:

* Draft appears for a teammate to review/edit/send
* Human stays in control of final outbound message

### 3) AI **auto-sends**

This happens when confidence meets/exceeds your selected threshold and auto-send is allowed.

Typical result:

* Response is treated as safe enough to send automatically
* Faster response times with less manual effort

***

## When the agent won’t reply automatically (common reasons)

Even with assignment configured, auto-replies may not occur for specific messages:

* Conversation is not assigned to an agent workflow path
* Message is classified as notification/system-style email
* Message is internal/non-customer
* Billing/trial access for AI resolution is unavailable
* Confidence falls into escalate-or-review paths instead of auto-send

This is expected safety behavior, not failure.

***

## Recommended rollout (to build team confidence)

If your team is new to AI email automation:

1. Start with **High** or **Very high**
2. Review draft quality for a week
3. Add/adjust escalation rules and assignees
4. Move to **Medium** only after quality is consistently strong

<Tip>
  A gradual rollout helps teams trust the system while protecting customer experience.
</Tip>

***

## Additional email settings

### Escalation assignee

Who receives conversations when escalation is needed.

### Escalation rules

Specific triggers that force handoff to a human teammate.

<Frame>
  <img src="https://mintcdn.com/weav-a01be0f7/reJWL8GwUmMMtmdB/images/Screenshot2026-02-28at8.03.53AM-1.png?fit=max&auto=format&n=reJWL8GwUmMMtmdB&q=85&s=d6927b78ab40b2a30191707722c99474" alt="Screenshot2026 02 28at8 03 53AM 1" width="1114" height="1056" data-path="images/Screenshot2026-02-28at8.03.53AM-1.png" />
</Frame>

### Signature

Appended signature format for agent-generated email content (supports using `{agent_name}` as a variable which gets replaced by the name of the agent in the signature).

### Notice

Optional banner text shown at the top of agent emails (hidden, first email only, or all emails). This is helpful for instances when you want emails to always show a notice so you don't have to repeat yourself. This is helpful for things like holiday promotions or communicating that you're aware of an outage happening.

***

## Best practices

* Keep exactly one clear owner for email assignment
* Use conservative thresholds first, then loosen gradually
* Treat drafts as a training signal: edit patterns tell you what to improve
* Pair auto-send with strong escalation coverage for sensitive topics
* Revisit threshold monthly as your agent quality improves
