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Introduction

Anyia

AI-Powered Technical & Behavioral Interviewer

Automating and enhancing the talent selection process using state-of-the-art conversational LLMs, objective automated scoring, and real-time audio analytics.

Team Members:
Juan Manuel CanovasMariaElena ArroyoMauricio CiroRodolfo JarquinSalvador Gonzalez
Anyone AI • 2026
AI
Prototype MVP

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Topic 01

The Problem: Recruitment Inefficiency

Traditional recruitment workflows suffer from massive inefficiencies and human bias that cost time, money, and candidate satisfaction.

Time-Consuming

Designing specific questionnaires for every single job profile manually takes hours.

Subjective Bias

Human evaluations suffer from inconsistency, lack of standards, and subjective assessment.

Topic 02

The Inputs: Job Profiles & Resumes

Rather than relying on massive generic datasets, the system leverages structured business inputs to dynamically personalize the interview process.

JD
Job Profiles

Key competencies, technical prompts, and parameters.

CV
Candidate Resumes

Skills, past experience, and educational background.

Topic 03

Flow of Agent 1

Inputs

CV / Profile
Role Description
Level & Skills
Company Information

Agent 1

The Interviewer
LLM
Analyze the context
Plan the interview
Generate questions
Evaluate answers
Adapt and go deeper

Real-Time Interview

Q: "How would you optimize this complex SQL query?"
A: "I would use indexes and optimized..."
Q: "What impact would this have on large-scale data volumes?"
A: "It would improve the execution plan..."

Continuous Feedback Loop

The LLM dynamically adjusts the next question based on the candidate's answer.

Topic 04

Agent 2: The Evaluator

An isolated agent that guarantees objectivity by grading candidate responses, extracting analytics, and delivering a standardized report.

Automated Rubric Scores:
Technical Competence85%
Communication Skills90%
Job Description Alignment78%
Topic 05

Business Impact & Feasibility

1. Feasible Architecture

Technical Feasibility
INTEGRATIONAPI / Local LLMs
INFRA COSTMinimized (No Scratch training)
STACKDocker Containers
  • Integrates existing LLM APIs and open-source models.
  • Reduces operational complexity and initial infra setup.
  • Cloud-based container orchestration scales instantly.

2. Recruiter Feedback Loop

Quality Calibration
Recruiter Quality Assessment
Agent 2
Improvement
  • Recruiters rate quality of AI evaluations (5-star scoring).
  • Agent 2 analyzes conversations against recruiter feedback.
  • Continuously calibrates and improves assessments over time.

3. Business & Hiring Impact

Strategic Value
Time-To-Hire-75%
Evaluations100% Standardized
  • Cuts candidate screening and initial interview time.
  • Enforces consistent, objective assessment across profiles.
  • Recruiters focus on final decision-making, not manual filters.

Thank You

Anyia: Transforming Talent Selection

Presented by Anyone AI Team Members. Ready to explore the candidate careers portal?

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Institution: Anyone AI • Final Project