The following combination of Runway's features is recommended for organizations with large-scale annual intern recruitment needs:
- CV pool pre-screening:Create a talent pool of interns for the season 3 months in advance, upload resumes of outstanding interns from previous years as benchmark samples, and the system will automatically screen out candidates with similar traits.
- Automated assessment assembly line:Set up a three-stage funnel of technical written test → project review → culture matching, and after each link is automatically scored by AI, only the candidates with the top 30% composite score will be scheduled for real-life interviews
- Batch offer management:Supports multiple comparison views for the same position, with the ability to view 10-15 candidates' skill heat maps and mentor evaluations in parallel, allowing for quick decision-making on offer prioritization.
Efficiency Data: Tests show that the solution reduces the average processing time for traditional school recruiting from 3 weeks to 72 hours and increases the 6-month retention rate of final hires by 42%.
This answer comes from the articleRunway: The Recruiting Tool That Intelligently Screens and Ranks CandidatesThe
May not be reproduced without permission:AI productivity tools " How can Runway be applied to improve productivity in a batch internship hiring scenario?
