Agentic Interviewer:

AI-Driven Voice Interviews for Scalable, Fair, and Automated Hiring

The MCP 1st Birthday Hackathon has unlocked a new era of innovation where multi-agent systems, powerful LLMs, and the Model Context Protocol demonstrate real, enterprise-grade capabilities. Our contribution to the Enterprise Applications Track is the Agentic Interviewer—an automated voice interview and evaluation system built entirely with agentic AI.

You can explore the live application here:"Demo of Agentic-Interviewer"

🧩 The Hiring Problem Today

Enterprises often struggle with the logistical nightmare of modern recruitment. HR departments face a barrage of challenges, including:

• Screening hundreds to thousands of CVs.
• Slow, repetitive early-stage filtering.
• Inconsistent evaluation across different interviewers.
• Human bias affecting hiring decisions.
• Candidates lacking realistic practice environments.

Mathematically, we can express the rising complexity of hiring as:

$$\text{Hiring Complexity}=O(N\times T\times I)\backslash text\{Hiring\; Complexity\}\; =\; O(N\; \backslash times\; T\; \backslash times\; I)$$

Where:

• $NN$ = number of applicants
• $TT$ = interview stages
• $II$ = interviewers required

As the number of applicants $NN$ grows, manual hiring quickly becomes unmanageable, leading to bottlenecks and lost talent.

🚀 Introducing Agentic Interviewer

The Agentic Interviewer is a fully automated AI system that conducts real-time voice interviews, evaluates responses using multiple agents, and generates a complete candidate scorecard—all without requiring a human interviewer present during the initial screening.

Key Features

🏗️ How the Agentic Interviewer Works

The system operates on a sophisticated pipeline designed to mimic—and improve upon—standard human interview workflows.

1. Upload Candidate CV & Job Description

The process begins when PDFs are parsed. The system organizes this raw text into structured data that the AI agents can process effectively.

2. Question Generation Crew

Three distinct agents collaborate to form the interview strategy:

• Technical Interview Agent: Focuses on hard skills.
• Behavioral/Culture-Fit Agent: Focuses on soft skills.
• Director Agent: Finalizes the interview plan to ensure a balanced assessment.

3. Live Voice Interview

A virtual interviewer conducts the session through FastRTC. The AI:

1. Speaks naturally and clearly.
2. Listens to candidate responses.
3. Asks relevant follow-up questions.
4. Logs all answers for subsequent evaluation.

4. Multi-Agent Evaluation Pipeline

Once the interview concludes, the data is passed to the evaluation crew:

• Technical Evaluator Agent scores domain knowledge.
• Behavioral Agent assesses communication skills.
• MCP Sentiment Tool analyzes the candidate's tone.
• Evaluation Director compiles a unified scorecard.

The Result: A comprehensive report containing a technical score, behavioral score, sentiment summary, and a final recommendation (Hire, No Hire, or Strong Hire).

🌟 Why This Approach Is a Game-Changer

For HR Teams & Enterprises

This system transforms the recruitment funnel. It offers automated screening, ensures unbiased decision-making, and creates a scalable interview pipeline that can handle N to infty applicants without additional human resource cost.

For Candidates

For job seekers, it provides realistic, role-specific practice interviews. This helps build confidence and improves performance in actual high-stakes interviews.

🎬 See the System in Action

Watch the full video walkthrough to see the agents interacting in real-time:

"Demo Youtube Video"

🔮 The Future of Recruitment

The Agentic Interviewer demonstrates what modern recruitment looks like: Automated, Fair, Standardized, and Scalable.

With potential future upgrades such as video analysis, multi-language support, psychometric scoring, and ATS integrations, this AI-driven system marks a major milestone in enterprise hiring innovation.