Your customer service/call center data is analyzed by our AI -a progressive learning algorithm- and automatically tagged without any manual work or training required.

Lang.ai learns from historical text data and is connected in real-time so new patterns are automatically discovered and shared with you.

You can start using Lang.ai by following these steps:

1) Import your historical text data or connect with Zendesk

Connect the historical data in your workflow. Lang.ai will automatically identify and propose smart tags based on the patterns it finds in those texts. They are presented in a hierarchical way so that you can see the big picture and still go into a more detailed view.

2) Select which tags are relevant to you based on your business criteria

You can then group and edit those suggested tags and choose which are going to be relevant to tag your ongoing data in real time, so that your data is automatically structured and you can be alerted, prioritize tickets or route them into the right person.

3) Import new data or activate real-time tagging

By uploading new datasets or integrating in real time for every new ticket or call you get, Lang.ai will automatically tag them (with the previously defined tag) and you can focus on building business processes on top of those tags. In the case of Zendesk Support, you can directly create automations to prioritize, assign to groups of agents, or include internal notes to assist them while resolving the tickets.

4) Automatically discover new tags

We know you launch new products and functionalities and you want to know which topics are arising in your conversations. Good news, are smart tags are not static! When connected in real time, our platform constantly suggests new tags by analyzing your ongoing data. You can be alerted and approve them to start using them as new data comes in.

Did this answer your question?