Weni Chats: Introduction to the Chats module

Sarah Pinheiro Updated by Sarah Pinheiro


Chats is the official human service module of the Weni platform. It was developed based on the needs and pain points of our customers, is native to every project on the Weni platform, and enables a self-service experience.

In the next sections you will be able to know more concepts and functions of this module.

User permissions

User permissions represent attributions referring to each user in the project, and in the Chats module, indicate the following roles:


It is the user who uses the Chats module to perform assistance, has minimum permission in the system and only views the Chats module and the Dashboards with their individual metrics. The calls directed to the agent are defined through the sector and queue in which he is included.

Service Manager

It is the user who manages the WeniChats service groups, has permission in the system to view settings related to the sector he manages, can view contacts in queues and perform calls. In the Dashboards, he visualizes the metrics of the sector in which he is a manager.


It is the user with all levels of permissions, creates sectors and delegates service managers to the sectors. In Dashboards you have an overview of the entire operation.

Contact informations

By clicking on the contact's photo or name in any area of ​​the conversation, it is possible to access the contact's information sidebar, where the contact's photo is presented in a larger size, data such as the channel through which the contact is talking, time of the last contact, function to transfer chat and media gallery of the contact.

Quick messages

Quick messages is a resource that provides the possibility of registering message templates so that they can be used quickly, when clicking on the quick messages button the user has access to the function's sidebar, where it is possible to view the messages, manage them and register a new one , a message can be used by clicking on the message, or by typing / followed by the shortcut of the message.

When selecting the desired message, the text registered in the message fills the text editor field.

You can use quick messages in two ways:

  • The first is like in the previous example, in which the agent opens the sidebar by clicking on the quick messages button and then clicks on the desired message.
  • The other option is by means of a shortcut, the agent when registering the message determines a keyword as a shortcut, to use it only with the keyboard the agent must type the key / (slash)

The user can navigate through the messages with the keyboard arrows and press enter to use the message, typing the shortcut text, the tool also performs the specific search:

Transfer Chat

The transfer chat function serves to direct the contact to a sector, queue or specific agent, this function can be accessed in the contact information area.

The user can search by the name of an agent, queue or sector, or can select a recipient from the list that opens, when confirming the transfer the contact is forwarded to the recipient.

Record and send audio

Through the buttons in the text box, the user can record an audio and send it, before sending it to the contact, the user can play the audio and finally send it.

User conversation history with chatbot

To facilitate the location of histories, Chats has 3 types of filters for now, they are:

  • Filtering by tags, which makes it possible to select tags and search for chats that were classified with those tags.
  • Filter by date, which makes it possible to determine a specific period or date to search for historic files.
  • Clear filters, there is also clear filters button

View history

The user will view the list of Chats in chronological order, from the most recent to the oldest, in this list it is possible to view the contact's photo, name, agent who provided the service, tags that were used to classify, date and a button to open the chat.

When viewing the contact history, the agent can see the beginning of the service, the history with the Bot and the chat events, finally the tags used to classify the chat itself.

How did we do?

Weni Chats: Setting Up Human Attendance