Skip to main content
The Chats section in the AI Textura platform’s left menu is a single place where the entire conversation history between your AI employees and clients is collected. Here you can see every dialog, monitor response quality, intervene in a conversation, reply to a client personally, and analyze every AI response. Think of it as a control room: all conversations are in front of you, you can see what is happening right now, and you can step in at any moment.
Chat list in the platform
The Chats section is accessible in two ways: via the left menu (all dialogs across all employees) or via the Live chat button in the AI employees list (dialogs for a specific employee).

Persona

How the employee runs a dialog and when to call a manager

Notifications

Escalation triggers and alerts

Quick Answers

Templates and chat management

Profiles

Client data inside the dialog

Why open Chats

  • Watch how AI employees communicate with clients
  • Quickly find a specific dialog by client name, channel, or employee
  • Intervene in a conversation when the situation requires a human
  • Handle escalations — cases when an employee handed the dialog to a manager
  • Evaluate AI employee performance on real conversations

Interface overview

Dialog list (left panel)

The left side of the screen displays a list of all chats. Each list item is a separate dialog with a client. Dialogs are sorted by time: the most recent ones appear at the top.

Conversation view (center panel)

Click any dialog in the list — the full conversation history opens on the right. Messages are displayed like a regular messenger: client on the left, employee on the right. Each message includes a timestamp. The chat header shows: client name, AI employee name (with {agent}), channel (· {channel}), and the menu button on the right — it opens the chat action menu. At the bottom of the window is the message input field — this is how a manager can reply to the client manually.
Open chat with a client

Chat info panel (right column)

The right column displays additional information about the current dialog: client profile, channel, employee name, and status. See Dialog details for more.
Chat info panel

Status indicators and quick buttons

Above the conversation feed and within the message stream, the platform shows several state indicators — they help you understand whether the AI employee is active in this dialog. Above the feed there are quick buttons:
The Clear history button does not delete the conversation from your chat history — it only resets the context the AI employee considers for its next reply. The same is done by the Wipe memory action in the action menu and by the text command (default delete all, see Account Settings).

Chat action menu

The button on the right side of the chat header opens the action menu — this is the central control panel for a specific dialog. It exposes commands that are not in the main interface.
Chat action menu (three-dot button)
Expanded chat action menu
Report (all messages) and Report (without archive) are especially useful when contacting Support: the ticket already includes the context, and the team can investigate faster. The same is done automatically by the thumbs-down button — it attaches a “Context report” on its own.

Per-message actions

Every AI employee message has its own set of buttons — they appear on hover or below the message.
Thumbs down is not just a rating. The button launches a full support flow: auto-diagnostics → instruction check → your problem description → automatic report attachment. Use it whenever the AI employee gave a wrong answer — the AI training team typically replies within 3 business days. See How to report an AI response.
Response analysis is the best debugging tool. Before changing the Persona or instructions, look at the analysis: maybe the AI simply didn’t call the right talent or didn’t find the document in the knowledge base.

Search and filtering

At the top of the dialog list there is a search bar (Search chat...). Enter a client name, keyword, or conversation fragment — the list filters in real time.
Shows dialogs for a specific AI employee only. Useful when you have multiple employees and want to analyze the work of one of them.
Filters by source: Telegram, amoCRM, Bitrix24, Wazzup, web widget, and any other connected channels. The channel list is built automatically from your connected channels.
Combine filters. For example, pick a specific employee and the Telegram channel — you’ll only see that employee’s Telegram conversations. This is convenient for analyzing performance in a specific channel.
Chat with accumulated conversation history

Manager intervention

One of the key capabilities of the Chats section is manual manager intervention in a conversation handled by an AI employee.

How to step in

1

Open the Chats section

From the left menu or via the Live chat button in the employees list.
2

Find the dialog

Use search or filters to find the dialog, then click on it.
3

Read the conversation history

Assess the context and decide whether intervention is needed.
4

Send a message

Type your message in the input field at the bottom and send it. The client will see your reply in their messenger.

What happens after intervention

As soon as the manager sends a message, the AI employee automatically pauses in that specific dialog. It will not interrupt the human.
Auto-resume after a pause is a configurable behavior. For 24/7 support, auto-start after a pause is almost always useful. For premium sales where a human touch matters, it is better to disable it.

Agent control commands

Managers can control an AI employee directly from a messenger using service commands. Commands are configured in the Additional Settings tab for each employee.
Start and stop commands are especially convenient for managers who work directly in a messenger. They can quickly enable or disable an employee in a specific chat without opening the AI Textura dashboard.

Escalation — when an employee hands off to a manager

Escalation is a situation when an AI employee recognizes it cannot or should not handle a request on its own and transfers the dialog to a human.

When escalation triggers

Escalation triggers in cases that you define in advance:
  • In the employee’s Persona (the “When to call a manager” or “Escalation” block)
  • In Notifications (triggers that send an alert and pause the chat)
  • In Quick Answers (actions of the “Chat management” type with a pause)

What it looks like for a manager

1

Receive a notification

The manager receives a notification in Telegram (or via webhook) that the employee handed off the dialog.
2

Find the dialog in Chats

In the Chats section, the dialog is displayed with a status indicating that intervention is needed.
3

Reply to the client

Open the conversation, read the context, and reply to the client.

Employee behavior on escalation


Dialog details

When you open a specific chat, in addition to the conversation history, additional information is available:
  • Client profile — filled fields: name, language, preferences, and any data the AI extracted from the conversation (see Profiles)
  • Channel — which messenger or CRM the conversation is going through
  • AI employee name — which employee is handling this dialog
  • Dialog status — whether the employee is active or paused
Full chat view with all panels

Live chat — public view

“Live chat” is a public chat page at /live/:id, accessible by direct link without logging into the platform. It is useful for:
  • Sharing a dialog with a colleague who doesn’t have a platform account.
  • Giving the client an alternative way to reply — straight from the page, without a messenger.
  • Testing AI responses in a regular web-chat format (handy when developing a prompt).
1

Open the chat

Go to the Chats section and pick the dialog.
2

Open the action menu

Click the button on the right of the chat header.
3

Choose 'Share link'

The platform will generate a public link to this chat.
4

Send the link

Copy the URL and send it to the recipient any way you like.
Public Live chat page
Anyone with the /live/:id link will see the chat contents. Don’t share the link if the dialog contains confidential client data.


Practical tips

Especially in the first days after launch. Browse conversations in the Chats section at least once a day during the first week.
Filter dialogs by a specific employee and review the last 10-15 conversations. This gives you an understanding of where the employee performs well and where adjustments to the persona or knowledge base are needed.
If you see that the employee is not responding correctly, jump in and reply yourself. The employee will automatically pause. After the conversation, adjust the settings.
Create triggers in the Notifications section for complaints, returns, VIP clients, and questions outside the employee’s competency. You’ll get an alert in Telegram and can quickly step in.
If your managers work in a messenger, configure start and stop commands in the Additional Settings tab and share them with the team.

FAQ

Chat history is kept on the platform. For some channels an Auto-clear history setting is available in the Channel tab — it allows automatic deletion of old dialogs.
Yes. When you send a message through the Chats section, the client receives it in whichever messenger they used to reach out. You don’t need to open Telegram or amoCRM — everything is handled from one window.
The client will receive both messages. It is recommended to coordinate within your team who handles a specific dialog to avoid duplication.
Three options: (1) wait 10-20 minutes — if auto-resume is configured, the employee will start on its own; (2) send the AI start command in the messenger; (3) manage from the platform interface.
Yes. The Chats section in the left menu shows dialogs across all employees. Use the employee filter to narrow the selection.
In most cases, the client sees messages from the same contact (bot or account) through which the AI employee was communicating. The transition is visually seamless for the client.
Yes. In the Additional Settings tab for each employee there is a Message limit setting — a cap on the number of messages in one chat per 24 hours. If no limit is set, there are no restrictions.
Click the thumbs down button on the specific AI message — it launches a 4-step review: auto-diagnostics → instruction check → your problem description → automatic context report attachment. The ticket is sent to the AI training team. See How to report an AI response for details.
Response analysis is a technical breakdown: which language was detected, which talents were called, what was found in the knowledge base, how the final decision was made. It only shows information — nothing is sent anywhere. Thumbs down uses the same diagnostics and submits it to support together with your description.
Open the menu → Share link. The platform generates a public /live/:id link — you can send it to anyone. See Live chat for details.
Three ways: (1) the Clear history button above the feed; (2) menu → Wipe memory; (3) the text command (default delete all) right in the chat. The command can be changed in Account Settings.