Documentation
Integration Guide

Jira Canvas Import

Import Jira Epics and Sprints directly onto your Forese.ai project canvas for visualization and Monte Carlo simulation.

What You Can Do

Pull Jira Epics or Sprints

Import directly into your project canvas

Visualize Dependencies

See connections between issues

Run Simulations

Monte Carlo analysis on imported data

Estimate Completion

Get confidence-level date ranges

View Work Breakdown

See hierarchical structure with React Flow

How to Import

1

Open Import Dialog

Open your project in the canvas editor, click the Import button in the toolbar, and select Import from Jira.

2

Select Source

Choose what to import: Select the Epic tab to browse and select epics, or the Sprint tab to choose from active or past sprints.

3

Preview Issues

Before importing, review the issues: see issue count, hierarchy, details (key, summary, status), story points and estimates.

4

Configure Options

Customize the import: include subtasks, dependencies, auto-estimate durations, set story points to days ratio, and choose layout.

5

Import

Click Import, wait for completion, and see imported nodes appear on your canvas.

Import Options

OptionDescriptionDefault
Include SubtasksImport subtasks as child nodesOn
Include DependenciesCreate edges from Jira linksOn
Auto-estimate DurationsConvert story points to durationOn
Story Points to DaysConversion ratio1.0
Position StrategyLayout algorithmHierarchical

Node & Status Mapping

Issue Types to Node Types

EpicEpicContainer node, groups children
StoryUser StoryWork node with duration
TaskTaskWork node with duration
BugTaskMarked with isBug: true
Sub-taskTaskChild of parent task

Status Mapping

To Dotodo
In Progressin-progress
Donedone
Blockedblocked

Duration Estimation

When Auto-estimate Durations is enabled, story points are converted to three-point estimates:

// Conversion Formula
Story Points x Conversion Ratio = Base Duration
Best Case = Base x 0.7
Most Likely = Base x 1.0
Worst Case = Base x 1.3

Example: 5 story points (ratio 1.0)

Best Case: 3.5 days | Most Likely: 5 days | Worst Case: 6.5 days

Custom Conversion Ratios

Fast Team (0.5)

~3 days per point. For experienced teams with few blockers.

Average (1.0)

~5 days per point. Standard velocity assumption.

Cautious (1.5)

~8 days per point. For complex projects or new teams.

Dependencies

Automatic Edge Creation

Jira "Blocks" links become dependency edges with Finish-to-Start relationships. The blocking issue becomes the source, and the blocked issue becomes the target.

Hierarchy Edges

Parent/child relationships create grouping: Epic contains Story, Story contains Subtask.

Running Simulations

1

Select Nodes

Select all imported nodes, or a specific subset for focused simulation.

2

Configure Simulation

Set iterations (1,000 - 10,000), enable dependencies for critical path, choose confidence levels (P50, P85, P95).

3

Review Results

View expected completion date ranges, critical path nodes, and risk analysis for highest variance items.

Pro Tip: Link to the Monte Carlo simulation guide for detailed instructions on interpreting results and optimizing your project timeline. Learn more

Troubleshooting

"No issues found"

  • Check Jira project permissions
  • Verify Epic/Sprint has issues assigned

Nodes overlapping

  • Use hierarchical layout for complex structures
  • Manually adjust positions after import

"Circular dependency detected"

  • Review Jira links for circular blocking
  • Remove one link to break cycle

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