Quick Overview
An anonymous leading technology company deployed an AI recruiter to handle initial screening and assessments of over 2,000 software engineering applicants monthly. The AI conducted asynchronous technical interviews using GPT-based models, rubric-based scoring, and generated consistent feedback. This automation reduced time-to-hire from 45 to 12 days, increased recruiter capacity by 67%, improved candidate quality by 34%, and lowered cost-per-hire by 61%.
Global Technology Firm (Anonymous)
Company Size
Large multinational
Revenue Range
Not publicly disclosed
Primary Challenge
Reducing time-to-hire and improving screening quality for high-volume technical recruitment
Key Metrics
\- Time-to-hire reduced from 45 to 12 days\- 67% increase in recruiter capacity\- 34% improvement in candidate quality\- 61% lower cost-per-hire
The Problem
Lengthy, manual technical screening delayed hiring and limited recruiter bandwidth
The Solution
AI multi-agent system using GPT-4 and large language models for asynchronous interviews, rubric scoring, and decision support
Results
\- Faster, more objective hiring\- Higher quality candidate selection\- Cost savings and efficiency gains
“The multi-agent AI system achieved 91% agreement with human experts and 4.6/5 candidate satisfaction.”
Research Team (Anonymous)
Details
Industry
Technology & SaaS
Departments
Human Resources & People Ops
Use Cases
Recruiting & Hiring
Tags
GenAI
NLP
Scalability
Team Efficiency
Time-Saving
AI Tools Used
No items found.
Sources
https://asendia.ai/blogs/how-ai-recruiters-are-transforming-the-hiring-landscape-in-2025-the-future-of-talent-acquisition
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