Skills & Training AI Case Study | HR Automation
Back to Case StudiesSkills Tracking & Training Recommendation Engine
Understand employee skills, identify gaps, and recommend internal training paths.
This HR AI automation case study explores Skills Tracking & Training Recommendation Engine. Tags: HR, AI Implementation, Reporting, Workflow Automation, OpenAI, Retool, AI Automation.
Significantly Improved
Team Allocation Accuracy
Reduced
External Hiring
Achieved
Career Growth Clarity
Overview
A technology company needed to understand employee skills, identify gaps, and recommend internal training paths. The system improved team allocation accuracy and reduced external hiring by identifying internal candidates.
Challenges
No clear picture of company-wide skill distribution
Training done ad hoc
Managers struggled to assign projects
Hiring decisions lacked data
What We Delivered
Skills graph backend with Python ingestion and Neo4j
Competency model with skills-gap detection and scoring
Self-assessment surveys for employees
Training recommendations based on role, skills, and career path
Manager view of team skills and gaps
AI summarization of strengths and project risk flagging
Tech Stack
Python, Neo4j, Node.js, PostgreSQL, Next.js, OpenAI
Tags
Results
Significantly Improved
Team Allocation Accuracy
Reduced
External Hiring
Achieved
Career Growth Clarity
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