AI Scoring is a on premise-based augmented analytics service that helps organisations monitor workforce outcomes, compliance risk, and worker wellbeing using data-driven scoring and forecasting. The solution automates end-to-end processing: it performs daily data extraction with a rolling 30-day lookback to capture late updates, applies standardised scoring schemes to generate performance scores and a wellbeing/happiness index, and publishes results through a web application and structured datasets for dashboards and reporting.
Key features include automated data cleansing and quality controls, multi-dimensional indicator scoring (e.g., retention, compliance, commitment, productivity, discipline, motivation and physical fitness), sector benchmarking that compares company performance against industry peers with automatic peer grouping, branch-level comparison with delta analysis against company averages for internal accountability, and governance-friendly reporting with both historical trends and "latest status" views. The platform also supports risk signals such as complaint and event summaries to help stakeholders detect emerging issues early. For prediction, AI Scoring uses time-aware machine learning trained with walk-forward validation to forecast next-month performance labels. It maintains two model families—company-specific models and indicator-set models—so the system can still provide forecasts when organisation-level data is limited. Forecasts include confidence estimates where available.
AI Scoring enables evidence-based workforce planning, early intervention for at-risk groups, improved resource prioritisation, and more transparent, auditable decision support. Target users include government-linked workforce programmes, regulators and compliance teams, HR and operations units, and analytics teams that require scalable monitoring of workforce performance and wellbeing in an operational environment.
