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Development of a Predictive AI Model for Employee Engagement Analytics

edvantis.com

Human Resources

Information technology

Challenge in Predictive Workforce Analytics

The client requires a custom predictive AI model to measure employee engagement, loyalty, and retention levels using collected datasets. Existing solutions lack the specificity to analyze daily interactions and forecast satisfaction metrics within a fixed budget and timeframe.

About the Client

An emerging talent technology vendor in the Americas specializing in AI-driven workforce analytics solutions

Key Project Goals

Develop a custom predictive AI model for employee engagement analysis
Deliver a robust solution within 3+ months under fixed-price model
Ensure compliance with development best practices and security standards
Enable cloud-based deployment with scalable architecture

Core System Requirements

Automated data processing pipeline for 49+ datasets
Predictive modeling for employee satisfaction forecasting
API integration for third-party HR systems
Secure cloud deployment on Azure platform
Real-time engagement/retention/loyalty metrics dashboard

Technology Stack

Python

Flask

Azure

System Integrations

Existing HR information systems (HRIS)
Cloud-based data storage platforms
Enterprise security frameworks

Non-Functional Requirements

Scalable architecture for enterprise-level data volumes
Real-time processing performance optimization
Enterprise-grade data security and encryption
Compliance with GDPR and industry-specific regulations

Expected Business Impact

Enables data-driven workforce management through accurate engagement predictions, improves employee retention strategies by 40%, enhances product differentiation in talent technology market, and provides measurable ROI through reduced turnover costs and improved organizational performance analytics.