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What is Tempo Automation?

Tempo automation is all about making it easy for you to log your time in Tempo Timesheets. How does this work? Tempo gathers the activity data from when you work in different "providers", such as Jira, VS Code, and JetBrains. It also retrieves the event data from your connected Google or Office 365 Calendars so that you can easily see all your meetings, for example, in My Work.

Tempo then uses this data to create suggestions that you see as activity cards in My Work. If the suggestions are accurate, you can log your time to them with a single click. If the suggestions aren't quite right, you can easily edit them. And if they're not what you want, you can simply ignore them and not log time to them, or delete them altogether - the choice is yours.

To create even more intelligent suggestions based on your activities, Tempo is introducing the use of Artificial Intelligence (AI) models - see below for more information.

Tempo Activity Feed Automation

Tempo’s Activity Feed draws its information from a wide range of providers to create suggestions for you, including Google Calendar, Office 365 Calendar, Jira, Visual Studio Code (VS Code), and JetBrains. Generally speaking, working in one of these providers will trigger the creation of a suggestion that appears as an activity card in My Work.

When you're working with two activity sources at the same time, an algorithm calculates activities from the collected events.

See Connecting and Disconnecting Your Activity Providers for more information.

Provider

How it works

Provider

How it works

Google Calendar and Office 365 Calendar

When you connect your calendar to My Work, your calendar events are automatically transformed into activities that make up your Activity Feed (see Connecting Your External Calendars). You can then log time on these activity cards with a single click (see Logging Time to Your Activities).

While it is a best practice to add the Jira issue key in the title (if applicable), we also read the calendar description. If a Jira issue key is in the description, Tempo can associate that calendar event with the Jira issue.

Note that changes to My Work activities will not be reflected in your external calendar.

Jira

Jira issues show up as suggestions (activity cards) in My Work when you:

  • Create a Jira issue.

  • Edit a Jira issue (such as changing an assignee).

  • Comment within a Jira issue.

  • Transition the Jira issue through the workflow (changing the Status).

You can then log time on these activity cards with a single click (see Logging Time to Your Activities).

Tempo displays Jira activities in 15-minute increments. For example, if you work on 3 different Jira issues for a total of 15 minutes, Tempo Automation’s algorithm will intelligently display the most relevant ticket (of the 3 Jira issues). If you subsequently delete that activity, it will show you the next relevant ticket until you’ve deleted all the activities.

Visual Studio Code (VS Code)

When you install the VS Code Extension for Tempo Timesheets app, the time you spend on coding activities and changes made to files in selected git repositories from VS Code appear as suggestions (activity cards) in My Work. You can then log time on these activity cards with a single click (see Logging Time to Your Activities).

Events that will trigger an activity to appear in My Work include:

  • Saving your changes

  • Git repository-specific actions (commits/check-ins)

Tempo displays VS Code activities in 15-minute increments.

JetBrains

When you install the JetBrains Extension for Tempo Timesheets app, Tempo automatically detects the time you spend on coding activities and changes made to files in git repositories.

When you save a file in JetBrains or commit/checkout in git, the extension will post an event to the Tempo API containing the current branch name, timestamp, and a commit message (if there's a commit). You can then log time on these activities with a single click (see Logging Time to Your Activities).

 

How Tempo Uses Artificial Intelligence (AI) Models

Tempo is moving towards further automation of the time-logging process by introducing the use of Artificial Intelligence (AI) models. You will see a mix of AI model suggestions and other issue keys that you previously used to log time in My Work. These predictions are based on the Event Title, Event Description, and historical logged time of all Tempo Timesheets users.

The more you log your time, the better the predictions will be. This is because the AI model learns from behaviors and patterns of how people log time in Tempo Timesheets.

All data collected by Tempo is kept anonymous.

There are two areas in Tempo Timesheets where you'll notice the AI models at work:

  • Suggestions in the issue picker when you log your time

  • Predictions for the missing issue key in activity cards in My Work

Suggestions in Issue Picker

The Artificial Intelligence (AI) model predicts based on previously logged activities in your timesheet. As Tempo starts using AI models instead of rule-based engines, it will provide more precise predictions and make it even easier to log your time.

To find and select an issue:

  1. Open the Log Time form in any of the ways described in Logging Your Time.

    log-time-select-issue.png

     

  2. Click in the Search box to display the issue lists.

    You'll see a mix of AI model suggestions and other issue keys that you have previously used to log time. The issues that are predicted by the AI models and rule-based suggestions (a maximum of 4) are identified by lightning bolt icons at the top of the list.

    issue-_picker-_ml.jpg

     

  3. Select the correct issue to log time against it, or enter a different issue key if you don't see the one you want. This helps the AI models to learn from your actions.

Predictions for Missing Issue Keys

Sometimes the events coming from your connected Google or Office 365 Calendars have no Jira issue key specified in their title. These are known as incomplete activities in My Work and prevent you from logging time to all your activities in a single click - see Logging Time to Incomplete Activities for more information.

As the AI models learn, they become more confident about suggesting the correct Jira issue for an event. Once the AI models are confident, those suggestions appear at the top of the list in the issue picker, which makes logging your time faster and easier!

Even after predicting the missing issue key, an exclamation mark might appear if any missing custom attributes are mandatory.

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