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Validate academic promotion decisions with GPT-4o, policy rules, and Gmail

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Created by: Cheng Siong Chin || cschin

Cheng Siong Chin

Last update

Last update 4 hours ago

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How It Works

This workflow automates performance governance and policy compliance monitoring for HR leaders, talent managers, and organizational development teams across enterprises. It solves the challenge of maintaining consistent performance standards while ensuring human judgment on promotion and termination decisions. Scheduled triggers initiate governance cycles that fetch performance data and policy rules, then orchestrate specialized AI agents working in parallel: governance assessment evaluates policy adherence, performance validation verifies metric accuracy, and calibration analysis ensures rating consistency across departments. A policy compliance checker synthesizes findings and routes outcomes intelligently—approved promotions store automatically, while exceptions requiring HR review trigger human approval gates before case creation and email escalation.

Setup Steps

  1. Configure API credentials with Llama-3.1-70B-Instruct model access
  2. Set up schedule trigger aligned with review cycles (quarterly/annual)
  3. Configure decision routing logic for approved versus exception cases
  4. Connect Gmail for HR escalation alerts to designated reviewers
  5. Set up Google Sheets for storing approved promotions and audit trails

Prerequisites

API key, performance management system data access, Gmail account with app password

Use Cases

Annual performance review calibration, promotion decision validation

Customization

Integrate HRIS for live performance data, add custom policy rule engines

Benefits

Reduces governance review time by 70%, ensures consistent policy application