The Functionary

Challenge

The Functionary was facing a sharp increase in AI-generated resumes and highly optimized applications. Candidates often appeared strong on paper, but many could not demonstrate real capability in live interviews.

This created a breakdown in early-stage screening.

• Resume quality no longer reflected actual skill or applied knowledge  
• Candidates advanced without demonstrating real capability  
• First meaningful evaluation shifted to later interview stages  
• Scheduling delays slowed candidate progression and increased drop-off risk of strong candidates
  

As a result, the burden on domain experts increased significantly.  

• Senior team members were validating basic qualifications instead of deeper capability  
• Interview cycles slowed as more low-signal candidates entered the process  
• Screening costs increased without improving hiring quality  
• The risk of selecting the wrong candidate increased  

The team began exploring AI-based screening to restore early-stage validation, reduce expert dependency, and improve hiring efficiency.  

Why Existing AI Tools Didn’t Work

The Functionary evaluated several AI screening and interview tools, but most introduced new problems instead of solving the core issue.

• Over-indexed on communication scoring rather than role-relevant capability
• Assessed technical knowledge in isolation, without real-world application
• Could not evaluate problem-solving, reasoning, and communication together
• Relied on scoring models that were difficult to explain or validate

These limitations created additional operational and candidate experience challenges.

• Created unclear or one-sided candidate experiences with no ability to ask questions or understand next steps
• Required workflow changes or operated outside existing systems

The team needed a solution that strengthened early-stage evaluation without adding complexity or removing control.

The Solution

The Functionary partnered with Function AI, the maker of Right Hire, to implement a structured screening approach for technical and technical-adjacent roles.

The system was designed around three operational objectives:

• Minimize inefficient interviews through earlier qualification validation
• Maximize expert productivity by prioritizing stronger candidates
• Establish a fair, structured, and globally consistent evaluation standard

Right Hire introduced an AI structured first-round interview layer that fits into existing workflows and standardizes how candidates are evaluated before expert involvement. The process was designed to address both evaluation quality and candidate experience, removing scheduling friction and ensuring candidates engage with clear, role-relevant questions in a consistent format.

What changed operationally:

• AI Structured First-Round Interviews: Candidates complete a consistent, role-aligned interview before expert time is allocated  
• Consistent Candidate Evaluation: All candidates are assessed against predefined criteria, ensuring only those who demonstrate real capability move forward  
• Unified Scoring Framework: Technical capability, problem-solving, and communication are evaluated together in one structured model  
• Workflow Integration: The process runs within existing systems, improving screening without disrupting recruiter workflows  
• Candidate Experience: Structured, role-relevant interviews completed on demand, allowing candidates to respond clearly and at their own pace

KPIs

While the team is still building longer-term performance data, early operational results were clear.

• Speed: Removed early-stage hiring bottlenecks by filtering candidates before expert interviews
• Efficiency: Reduced time spent by senior team members on basic qualification screening  
• Quality: Improved alignment between candidate profiles and role requirements  
• Consistency: Standardized evaluation across roles, regions, and hiring managers
• Defensibility: Introduced structured, evidence-based scoring with clear breakdowns  

FAQs

Did it improve candidate quality, or just make things faster?
Both, but quality was the bigger change. Fewer unqualified candidates were making it through. Hiring managers saw better-aligned profiles, and some noted stronger performance during training compared to previous hires.

How did it fit into your existing workflow?
It fit into what was already in place. No major process changes or new systems to manage. It just replaced the early screening step with something more structured and consistent.

What was the candidate experience like?
More structured and less dependent on scheduling. Candidates completed the interview on their own time and moved through a consistent set of role-specific questions. Some initial hesitation was expected, but feedback was generally positive. Candidates said the questions were clear, the process felt focused, and they had more time to explain their answers than in a typical interview.