Nave for JiraTurn your Jira delivery data into evidence about flow, predictability and where work is slowing down.
14 days, no credit card.
Jira delivery analytics
See cycle time by workflow stage, waiting and blocked time, and the bottlenecks holding work up.
See aging work and items approaching or exceeding your normal delivery expectations.
Track cycle time, throughput, WIP, flow efficiency and variability over time.
Use Monte Carlo forecasting based on actual Jira throughput, not estimates.
How it works
Connect a board, map its workflow and use the resulting evidence to decide where to act next.
Choose the Jira board whose delivery flow you want to understand.
Map columns to workflow stages and mark the stages where work waits.
Nave computes flow metrics from the board’s existing delivery history.
Use the evidence to address constraints, forecast delivery and track improvement.
Diagram
Jira board columns
Nave workflow stages
Connect your Jira board and Nave turns its existing delivery history into flow metrics, so you don’t have to wait weeks to start learning from your data.
Jira
Manage issues, boards, projects and workflows where your teams already work. Jira remains where the work is managed.
Nave
Use Jira delivery history to answer system-level questions about flow, predictability, aging, bottlenecks, improvement and forecasting, without changing how teams manage work in Jira.
Find constraints
The Mobile Platform table shows, from Aug 3 to Sep 25, 2026, when 50%, 85%, and 95% of issues left each stage. Across the process, 85% finished within 21 days. At the 85th percentile, Ready for SIT took up to 6 days, Awaiting Release 7, and Development 6. Waiting stages equaled or exceeded active development.
Explore Cycle Time Breakdown
Current work
The AI Investigator reads computed flow metrics and points to the stage and work items behind a problem. Here, it flags WIP at 10 items versus a 53-day average of 5.56, and two items stalled in Ready for SIT for 5.37 days, past the 85th percentile. If the evidence doesn’t support a meaningful finding, it returns none.
The numbers are computed, not generated. The AI only reads them, so swap the model and the numbers don't change.
Explore AI Investigator
Plan realistically
Monte Carlo runs 10,000 trials using this team’s daily throughput from August 3 to September 25. It forecasts how many items will finish from September 30 to October 14 at 50%, 85% and 95% confidence. There are no story points or estimates, and the Continuous Forecasting dashboard recalculates daily.
Customer stories
“We are using Jira, and the main issue with it is that it doesn’t give us any visibility to flow metrics. The data is there, but we cannot actually see it in an easy way.”
Pawel LewinskiScrum Master and Accredited Kanban TrainerImproved delivery times by 30%
Read Pawel's story“This worked for a while but once the whole company started using Jira we felt the need to up our game, and this is when we discovered Nave.”
Reinaldo SimizuAgile Coach at MateraCut lead times by 4x
Read Matera's storyMeasure change
The Process Improvement dashboard uses natural process limits from your team’s own history to distinguish real signals from normal variation. Track cycle time, throughput, WIP, flow efficiency and variability over time without treating every change as meaningful.
Scale the view
Start with a team dashboard. Roll Jira teams into Services and Portfolios, place Jira teams alongside Azure DevOps teams in a Service, and compare performance over time across teams and services in Executive Dashboards.
Connect Jira
Log in with a click through OAuth 2.0. Nave only sees what your Jira account can see.
Connect Jira
A Jira administrator links Nave once. Users enter the Host URL to authorize. The instance must be internet-accessible; otherwise, upload CSV or JSON data or use the Nave API.
Read the setup guideNave reads board ID, name and columns; issue keys, summaries, priority, created and due dates; status changes; flagged or blocked time; assignee names and avatars; selected custom fields; and Jira links. Descriptions, comments and attachments are not included.
Each dashboard maps one Jira board. You map its columns to not started, in progress and done, then mark waiting stages so flow efficiency separates active time from waiting time.
Filter dashboards by issue type, labels and the custom fields you choose to bring into Nave.
Nave loads recent Jira history first, including three months of completed work by default. Choose an earlier date range to load older work.
Nave never accesses your Jira password. It never creates, changes or deletes issues, comments, boards or projects, and only sees what your account can see.
Choose not to store task names, a setting users cannot reverse. Contact Nave to hide all person-related fields from a Jira dashboard.
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