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.
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
Step 2 _ Intelligence
Here you should select your AI Lenses. Pick between 3 to 6 metrics to shape your Radar chart and performance score.
| Card Name | Description |
|---|---|
| Commitment & Delivery | Measures how consistently a team member delivers the work they commit to during each sprint, including completed work, carryovers, and estimates. |
| Resolution Quality | Looks at how effectively issues are resolved and whether they stay resolved. Considers reopened issues, recurring bugs, and incomplete fixes. |
| Scope Discipline | Measures how well a team member stays focused on planned work, manages priorities, and avoids unnecessary changes during a sprint. |
| Work Item Quality | Evaluates the quality and completeness of issues created by a team member, including clear descriptions, useful details, and well-defined requirements. |
| Process & Compliance | Measures how consistently a team member follows agreed workflows, completes required information, and follows team processes. |
| Ownership & Accountability | Looks at how actively a team member takes ownership of their work, from picking up tasks to completing them and proactively addressing problems. |
| Consistency & Productivity | Measures how consistently a team member contributes over time and identifies significant changes in their usual work patterns. |
| Initiative Rate | Highlights proactive behavior, such as identifying issues, suggesting improvements, creating work without being asked, and helping improve processes. |
| Team Contribution | Measures how a team member helps others succeed by unblocking teammates, sharing knowledge, creating useful documentation, and offering support. |
| Feedback Effectiveness | Evaluates how effectively a team member gives and receives feedback, responds to others, and uses feedback to improve their work. |
| Organizational Impact | Measures how broadly a team member’s work contributes beyond their immediate team, including collaboration and connections across the organization. |
| Incident Response & Ownership | Measures how actively a team member responds when issues occur, including response times, involvement in incidents, and follow-up after resolution. |
Step 3 _ Launch
Here you can control who gets eyes on these insights , choose the Visibility and click “ Launch Perspective ” :
After creating a Perspective, the system automatically displays a visualization of the relevant data and insights.
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:
The Resync AI button triggers the AI evaluation engine for a given Perspective. When you click it, it:
- Sends the Perspective’s configuration (selected users/teams, JQL scope, AI Evaluation Window, and chosen AI Lenses) to Rovo
- Rovo processes the Jira activity data through those lenses (e.g., Delivery Reliability, Resolution Quality, etc.)
- Generates performance scores, radar charts, and AI insights for the users in scope
- 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:
Perspective Views
You can change the current perspective view from the tabs:
- Space
- Chart
- Trends
- Health
- Insights
- Today
- Week
- Month
- Window
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.
By clicking Insights button, it opens a Rovo chat session:
- Rovo opens with the context pre-loaded — the user’s activity data, the Perspective config (JQL scope, evaluation window, selected AI Lenses)
- Rovo then generates the narrative analysis as a chat response — contribution patterns, trends, outliers, explanations
- 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:
