Leave Request Routing

This use case shows how NeuronFlow can handle leave approvals where the outcome depends on manager review, policy checks, calendar conflicts, and clear employee feedback.

Where This Fits

This workflow is useful when:

• leave requests arrive from forms, inboxes, or HR tools
• different teams follow slightly different approval rules
• some requests need a second reviewer from HR or leadership
• managers often send requests back for clarification or date changes

Typical Workflow Shape

1. A leave form or inbox event starts the workflow.
2. A Set or Code node normalizes the employee request.
3. AI or rules evaluate duration, overlap risk, and policy exceptions.
4. A policy object is built for the approval step.
5. Approval Group routes the request to the direct manager or to a wider approval group when needed.
6. The reviewer can approve, reject, or request changes with comments.
7. If changes are requested, the workflow returns the request with the manager note so the employee can correct it.
8. Once approved, downstream nodes can notify HR, update calendars, or trigger the next internal process.

Best Node Pattern

• Trigger or Webhook: receive the leave request from a form, inbox workflow, or HR system callback
• Set or Code: normalize dates, leave type, requester details, and overlap checks into one request object
• AI Agent: summarize the request and flag unusual policy signals or missing context
• Switch: classify standard leave vs exception or conflict paths
• Set: prepare structured reviewer policy data
• Approval Group: manage manager or HR review, comments, and revision loops
• Tool or HTTP Request: update Google Calendar, Outlook Calendar, or the HR system after approval
• Tool: send the final outcome to the employee and HR in Gmail, Slack, Microsoft Teams, or SMTP Email

Approval Policy Example

{
  "reviewers": [
    { "name": "Direct Manager", "email": "manager@example.com" }
  ],
  "fallback_reviewers": [
    { "name": "HR Reviewer", "email": "hr@example.com" }
  ],
  "review_mode": "all",
  "allow_comments": true,
  "allow_request_changes": true,
  "require_comment_on_reject": true,
  "require_comment_on_request_changes": true,
  "routing_metadata": {
    "severity": "medium",
    "routing_reason": "Leave overlaps with another approved absence",
    "recommended_by": "rule"
  }
}

Why NeuronFlow Fits Well

• Employees get specific comments instead of vague rejections.
• Approval policy can change by overlap risk, leave type, or team rules.
• Revision loops let the process continue safely after corrections.
• Final approval data remains traceable in execution history and audit review.

What Success Looks Like

Managers handle exceptions without losing structure, employees receive actionable feedback when changes are needed, and HR can review a clean record of the whole decision path later.