Internal Mobility Recommendation uses AI to surface relevant open roles to employees considering internal moves, enabling higher internal fill rates, by matching employee profiles to role requirements and career trajectory patterns, across talent marketplace platforms.
Employees seeking internal career moves lack visibility of relevant opportunities across business units, and hiring managers cannot efficiently identify internal candidates, resulting in under-utilised internal talent and avoidable external hiring costs.
A matching and ranking model compares employee skill and experience profiles against open internal requisitions, generates a ranked opportunity list for the employee, and surfaces employee profiles to hiring managers for internal consideration before external posting.
Increase in internal fill rate for open roles and reduction in cost-per-hire for positions filled internally.
No verified references yet.
Applied AI for Enterprise
Ready to explore this use case for your organisation?
Knowledge assistants leverage AI to provide instant, contextual access to organizational knowledge, improving employee productivity and decision-making. By integrating diverse data sources and advanced AI methods like agentic AI and retriev
Pay Equity Anomaly Detection uses AI to identify statistically significant pay disparities across employee groups performing comparable work, enabling proactive remediation, by analysing compensation distributions against role, level, performance, tenure, and demographic attributes, across annual compensation review cycles.
Candidate Eligibility Classification uses AI to apply screening criteria consistently, enabling fairer high-volume hiring, by classifying applications against role requirements, across candidate screening and selection.