Chat archival was only intended as the first step in development. We see it as a tool that increases efficiency of collaboration in modern diverse and distributed teams. So, we spent last month brainstorming various ideas about what can help in reaching this goal.

When you have a live, constantly updating archive of your team’s chats, there’s a great deal of information hidden inside it. Who is talking a lot? Who talks to whom? What are the individual communication patters?

Answers to questions like this contain insights into team’s productivity, effectiveness, and, in essence, into teamwork.

Consider the following scenarios:

  • A new hire can’t communicate well with the rest of the team because the team usually talks in Slack with paragraph-length messages and slow pace, and the new hire treats Slack like text messages: short notifications on urgent things.

  • There is a hidden conflict within a distributed team, and two team members don’t talk to each other (and this can only be seen from chat logs).

  • There is not enough communication between teams (like development and QA), and this hurts the overall performance.

We know that chat logs can be a powerful resource to identify and resolve such issues., having its direct integration with team chats, happens to be in the right place to analyze the chat logs.

With this in mind, we’ve been talking with team leaders, conducting surveys and interviews, finding out what kind of insight can help team leaders and managers to better understand and boost their teams.

We’ve put up a page at with more information about the reports and insight that will be provided by it.

If this can be interesting for you, feel free to reach us. As this is all about data mining, it’s means always not having enough data to analyze (but we’re bound by our Privacy Policy, and can’t use archives uploaded by our users). You can help shaping this idea into a product which can be helpful.