Remove the key frustration of Slack users: Tired of micro-managing unread messages in multiple channels in Slack. Recap/digest messages intelligently for users.

crying slackbot

What it does

Using a slash command, Taz creates a digest of the unread messages that are:

  • Trending based on emoticons
  • Directly or undirectly mentionned to you
  • Most talked about topics

trending messages example

How we built it

Having the problem clearly defined, our first priority was to brainstorm a backlog of features and figure out which were part of our minimal viable product (MVP) and which were nice to have that we could squeeze in at the end to wow the crowd.

We then went on an epic journey to find the brand we would give our bot. This would in turn give us a better idea how to design, market and bring it some appeal.

On a technical note, a Slack command sends data to our Azure web API endpoint. This endpoint then crunches your Slack data and figures out the unread messages and direct/undirect mentions. This formatted data is sent as a beautiful digest in the taz bot instant messaging channel.

Challenges we ran into

  • Generating usable dummy data
  • Splitting tasks equally to leverage the team
  • Formatting and rendering the Slack post
  • Slack throttling our messages
  • Don't always trust a Slack API wrapper

Accomplishments that we're proud of

What we learned

  • Don't cheap out on marketing/design strategies
  • Organizing on a tight deadline
  • Prioritizing features for an MVP
  • Sleep is a luxury

What's next for taz

  • Machine learning; intelligently process message data
  • Activity heatmap
  • Natural language recognition
  • Multlingual support
+ 16 more
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