User Guide - Pulse AI

Pulse AI appears to center on a dedicated page and related reporting experience within User Activity Audit Log. The broader product already supports rich audit exploration, and Pulse AI builds on that with AI-oriented interpretation and leaderboard views.

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Create Perspective

Before you can start using Pulse AI, you must first create a Perspective. Click the “Create Perspective” button to proceed. Here you need to fill these fields:

Step 1 _ Context

  • Name

  • Icon

  • People and Scope

    • Select Users
    • Select Groups
    • Select Teams
    • Select People In Project
  • JQL

    • Filter the Jira scope for this Perspective
  • AI Evaluation Window

    • Days
    • Weeks
    • Months

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Step 2 _ Intelligence

Here you should select your AI Lenses. Pick between 3 to 6 metrics to shape your Radar chart and performance score.

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Card Name Description
Delivery Reliability Tracks whether a contributor ships what they commit to each sprint. Measures commitment rate, carryovers, and estimation discipline.
Resolution Quality Checks whether resolved issues stay resolved. Tracks reopen rates, recurring bugs, and silent closes.
Scope Discipline Detects scope creep, mid-sprint re-additions, and context switching. Rewards ruthless prioritization and de-scoping behavior.
Work Item Quality Scores the hygiene of Jira issues created by a contributor. Rewards completeness and acceptance criteria. Penalizes vague issues.
Process Adherence Measures whether contributors follow agreed workflows, fill mandatory fields, and participate in retrospectives. Flags policy violations.
Ownership Depth Detects true ownership behavior: self-assignment, end-to-end issue completion, proactive updates, and self-discovered problem reports.
Velocity Consistency Measures how predictably productive a contributor is week over week. Detects boom/bust patterns and unexplained dead weeks.
Initiative Rate Measures proactive behavior: self-discovered issues, RFCs written, process improvement contributions, and out-of-team work.
Team Amplifier Identifies force-multiplier contributors who unblock others, create shared documentation, and proactively seek out or help.
Feedback Loop Evaluates the balance of giving and receiving feedback. Tracks comment quality, response times, and whether feedback is incorporated.
Organizational Reach Maps how broadly a contributor’s work touches the organization. Identifies connectors versus siloed specialists.
Incident Ownership Rewards who shows up when things break. Tracks P1/P2 response times, voluntary incident involvement, and post-mortem authorship.

Step 3 _ Launch

Here you can control who gets eyes on these insights , choose the Visibility and click “ Launch Perspective ” :

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After creating a Perspective, the system automatically displays a visualization of the relevant data and insights.

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Scoring Model

Pulse AI scores are built on two layers working together:

Layer 1 — Base Performance Score (configurable weights)

Each user gets a Performance Score calculated from their raw Jira activity within the Perspective’s scope (JQL filter + AI Evaluation Window). The inputs are:

Signal What it measures
Activity volume Total count of tracked actions
Activity type weight Each type (comments, status transitions, field updates, issue creation, assignment changes, worklogs) has a configurable weight
Time distribution How activity spreads across the evaluation window (consistency vs spikes)
Cross-project participation Breadth of contribution across projects

The formula is visible and configurable by admins — meaning organizations set the weights per activity type to match their priorities. The system is explicitly designed to be auditable: every score is traceable back to the underlying activities, applied weights, and time range.

Layer 2 — AI Lenses (Rovo evaluation)

On top of the base score, admins pick 3 to 6 AI Lenses that form the radar chart. Each lens is an independent AI-evaluated dimension:

  • Delivery Reliability — commitment rate, carryovers, estimation discipline
  • Resolution Quality — reopen rates, recurring bugs, silent closes
  • Scope Discipline — scope creep, mid-sprint re-additions, context switching
  • Work Item Quality — issue hygiene, completeness, acceptance criteria
  • Process Adherence — workflow compliance, mandatory fields, retro participation
  • Ownership Depth — self-assignment, end-to-end completion, proactive updates
  • Velocity Consistency — week-over-week predictability, boom/bust detection
  • Initiative Rate — self-discovered issues, RFCs, process improvements
  • Team Amplifier — unblocking others, shared docs, proactive help
  • Feedback Loop — comment quality, response times, feedback incorporation
  • Organizational Reach — cross-org contribution breadth
  • Incident Ownership — P1/P2 response, voluntary involvement, post-mortem authorship

Rovo processes the Jira activity data through these lenses and produces per-user scores for each. The combined lens scores shape the radar chart visualization.

Re sync AI

Once the generated visualization is ready, you can see The Resync AI button:

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The Resync AI button triggers the AI evaluation engine for a given Perspective. When you click it, it:

  1. Sends the Perspective’s configuration (selected users/teams, JQL scope, AI Evaluation Window, and chosen AI Lenses) to Rovo
  2. Rovo processes the Jira activity data through those lenses (e.g., Delivery Reliability, Resolution Quality, etc.)
  3. Generates performance scores, radar charts, and AI insights for the users in scope
  4. After completion, you click the Refresh button to load the results on the Perspective page

Every time the underlying data changes — new activity is logged, the evaluation window shifts, or you modify the Perspective config — the AI scores need to be recalculated. The Resync AI button lets you manually trigger that recalculation on demand.

Users land on the Perspective page and have to manually click Sync AI → confirm in Rovo → Refresh.

Actions

Create New Perspective

You can create a new Perspective by clicking “ Create New “ button:

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Perspective Views

You can change the current perspective view from the tabs:

  • Space
  • Chart
  • Trends
  • Health
  • Insights
  • Today
  • Week
  • Month
  • Window

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Insights

Insights button is essentially a contextual Rovo entry point — it launches Rovo with all the relevant Pulse data already loaded so you don’t have to explain the context yourself.

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By clicking Insights button, it opens a Rovo chat session:

  1. Rovo opens with the context pre-loaded — the user’s activity data, the Perspective config (JQL scope, evaluation window, selected AI Lenses)
  2. Rovo then generates the narrative analysis as a chat response — contribution patterns, trends, outliers, explanations
  3. Because it’s a Rovo conversation, you can ask follow-up questions — drill deeper into specific lenses, compare time periods, ask “why did their score drop?”, etc.

Why Rovo:

This design means Insights is interactive, not static. Instead of a fixed summary card, you get a conversational AI session where you can:

  • Ask clarifying questions about a specific score dimension
  • Request comparisons (“how does this compare to last sprint?”)
  • Get deeper context (“what caused the drop in Delivery Reliability?”)
  • Ask for actionable suggestions (“what should I discuss in our 1:1?”)

Edit & Delete Current Perspective

Yo can Edit or Delete current Perspective by clicking three dots next to the selected Perspective:

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