Airgentic Help
This module covers human monitoring and intervention in Airgentic conversations. Read this when you want to set up live monitoring, understand when to intervene, or plan escalation workflows.
Human Handoff lets your team:
This enables a hybrid model where AI handles most interactions, but humans can step in when needed.
Go to Human Handoff in the admin console. The screen maintains a live connection and updates automatically.
Each service can run in one of three modes:
| Aspect | Description |
|---|---|
| AI behaviour | Handles all conversations |
| Human involvement | None — no monitoring, no intervention |
| When to use | Fully autonomous operation, no support staff availability |
| Aspect | Description |
|---|---|
| AI behaviour | Responds normally to all conversations |
| Human involvement | Can monitor, see flags, and take over when needed |
| When to use | Standard operation — AI handles most, humans available for escalation |
This is the most common mode for services with any human support capability.
| Aspect | Description |
|---|---|
| AI behaviour | Disabled — does not answer questions. After the first customer message, a one-time holding notice is sent (“A human assistant will be with you shortly.”) |
| Human involvement | Must respond to every conversation |
| When to use | Rare — perhaps during critical incidents or specific use cases |
Switching modes:
- Change mode per service using the button group
- Change all services at once with Apply to all services
Services can follow a weekly staffed-hours policy instead of leaving the radios on one mode all day. Open Hours in Desk settings. Typical setup:
| When | Mode |
|---|---|
| Selected weekdays, inside the start/end times | Human-Supported AI (Human Only is available) |
| Nights, weekends, and closed dates | AI Only (Human-Supported is available) |
Choose a timezone, start and end times, weekdays, closed dates (single days or inclusive ranges), and the in-hours vs outside-hours modes. Overnight windows are not supported. Public holidays are not imported automatically.
The live mode is evaluated when a customer message arrives. Clicking a mode radio while a schedule is on asks how long the override should last (until the next scheduled change, until a chosen time, or until you turn the schedule off) and does not rewrite the saved hours. Turning the schedule off snapshots the current live mode as the new manual setting.
Only admins can edit hours. Agents see the live mode but cannot change the schedule.
A playbook can overlay a different mode for one session without changing the Hours control. The Hours / Redis override still wins. Playbook conditions that match hours use the schedule result before that overlay.
Auto-assign is optional and off by default. When a service is in Human Only or Human-Supported AI, an Auto-assign switch appears next to the mode controls.
| Mode | What is queued |
|---|---|
| Human Only | Every new customer conversation |
| Human-Supported AI | Only conversations that need a human (help requested, thumbs down, non-answer, or negative sentiment) |
Agents join the pool when they have Human Handoff open and Available is on. Auto-assign fills My chats up to 10 concurrent claims; an agent at that cap is skipped until they hand a chat back, transfer it, or go Away. Manual Take Over can exceed the cap. Assignment does not expire after five minutes. Auto-assign toasts and marks the row unread; it does not open the transcript. The oldest waiting conversation is claimed for the next agent with capacity. If nobody is free, the conversation stays in Queued. Agents can still Take Over an unclaimed card themselves.
Toast notifications do not put you in the pool — the Human Handoff page must be open. Only admins can turn Auto-assign on or off.
Give live-support staff the Agent role instead of Customer Admin. They land on Human Handoff after sign-in, can work the inbox and Insights, and cannot change modes, hours, Auto-assign, or other configuration. See User Management.
The desk is a three-column workspace. The left column buckets conversations:
| Bucket | Meaning |
|---|---|
| My chats | Assigned to you. Switching rows does not notify the student. |
| Queued | Waiting for a human (escalation, Human Only, or returned to the queue). Not the assignment cap. |
| Monitoring | AI is still answering. New Human-Supported chats start here. |
| Recent | Closed or reset threads from the last 48 hours (separate tab, read-only). |
Each card still shows location, opening question, time, message count, and tags, plus a small service chip. Queued chats also show how long the customer has been waiting; those cards turn amber then red at the times set in Desk settings.
Search, Filter, and Sort sit above the inbox. Hidden chats still count in need attention, so a filter cannot hide an escalation.
Conversations requiring attention are highlighted with a red pulsing border and coloured badge:
| Flag | Trigger |
|---|---|
| Thumbs Down | User gave a negative rating |
| Non-Answer | AI couldn't answer the question |
| Negative Feedback | Negative sentiment detected |
| Help Requested | User asked for a human |
These conversations increment the need attention banner above the inbox and the count on the browser tab.
Why flags matter:
- They surface the conversations most likely to need help
- They help you prioritise limited attention
- They indicate potential service quality issues
Click any conversation card to open the transcript in the workspace. Switching My chats does not claim, release, or notify the student.
Click Take over to:
1. Claim the conversation
2. Pause the AI (it stops responding)
3. Notify the customer that a human has joined (in Human-Supported AI)
Once you've taken over:
- Type a reply, click Generate to draft the same response the customer would have seen, or insert a saved reply
- Use Note for a private message that only other agents can see
- Press Enter to send; use Shift + Enter for a new line
- Your messages appear as a human-agent reply — citations stay in the admin Sources list
- Generating a draft counts toward usage; typing the reply yourself does not
Once a human has stepped in, the AI stays paused until Hand back to AI.
| Action | Effect |
|---|---|
| Hand back to AI | Two-click confirm in Human-Supported AI. The AI resumes; the student is notified. |
| Transfer | Pass to a colleague currently on the desk. The student sees one line naming them. |
| Return to queue | Unclaim, stay paused, no student message. Auto-assign may pick someone else. |
Idle time does not drop the claim. Recent conversations are read-only.
If another agent has already claimed a conversation:
- The Take Over button shows their name and is disabled
- You can wait for them to release it, or they can Transfer or Return to queue so you can take over
The escalate_to_human global function provides programmatic escalation:
This creates an asynchronous handoff — the user doesn't wait for a live agent.
For real-time escalation:
This requires someone actively monitoring.
| Approach | Works when |
|---|---|
| No escalation | AI handles everything; users contact support separately if needed |
| Async escalation | Staff aren't available for live chat; email follow-up is acceptable |
| Live escalation | Staff monitor during business hours; users expect real-time response |
| Hybrid | Staffed hours for live cover, AI Only or async email outside hours |
Do intervene when:
- User is clearly frustrated and needs human empathy
- AI is stuck in a loop or giving obviously wrong answers
- The question requires authoritative human judgment
- User explicitly asks for a human
- High-stakes or sensitive situations
Don't intervene when:
- AI is handling the conversation well
- You'd just be saying what the AI said
- The user is exploring and doesn't need help
- Intervening would slow down resolution
You don't have to stay on the Human Handoff page:
(3) Human HandoffFrom Insights, monitor:
| Metric | What it indicates |
|---|---|
| Non-Answer rate | Content gaps or prompt issues |
| Thumbs down rate | User satisfaction problems |
| Negative sentiment rate | Overall experience quality |
| Escalation requests | User expectation for human support |
High rates in any of these suggest investigation and improvement.
Back to: Optional Deep-Dives