HR AI Tool

AI-Powered Interview & CV Analysis for Data-Driven Hiring

Internal AI-powered platform that analyzes interviews and CVs to deliver data-driven hiring insights, automating candidate evaluation, reducing bias, and improving recruitment efficiency with NLP, emotion detection, and skill matching.

problem
Recruiters and HR teams spend hours manually screening
CVs and evaluating interview answers.

Inefficient

hours lost reviewing CVs and interviews

Inconsistent

decisions vary across recruiters

Unscalable

slows down growth and team building

solution
AI System for Support Candidate Evaluation

Tool that automatically analyzes CVs and
video interviews using:

CV Analysis

Skill extraction (tech + soft)

Career trajectory scoring

AI-matching to job description

Gaps, red flags, inconsistencies

Seniority & potential estimation

Myers–Briggs Type Indicator and matching

with current team structure

Output: Structured JSON + ranked candidate fit

CV Analysis

Skill extraction (tech + soft)

Career trajectory scoring

AI-matching to job description

Gaps, red flags, inconsistencies

Seniority & potential estimation

Myers–Briggs Type Indicator and matching

with current team structure

Output: Structured JSON + ranked candidate fit

Video Interview Analysis

Transcription of the full interview

Big Five Personality Model scoring

Emotion recognition (facial + vocal tone)

STAR method analysis
(Situation, Task, Action, Result)

Question-answer pair grading

Visualized report + PDF summ

Video Interview Analysis

Transcription of the full interview

Big Five Personality Model scoring

Emotion recognition (facial + vocal tone)

STAR method analysis
(Situation, Task, Action, Result)

Question-answer pair grading

Visualized report + PDF summ

Business Impact

Time-to-Hire

Reduced by 60% through AI-driven shortlisting and role matching

HR Costs

cut by 40% by streamlining candidate vetting and interview cycles

Hiring accuracy

Improved by 3x via skill-to-role alignment and trajectory scoring

Bias

Improved by 3x via skill-to-role alignment and trajectory scoring

C-level insight

Clear, actionable reports for faster executive decision-making

Retention signal

Candidates like CE, who passed AI-evaluated test periods, show 2x lower early attrition rates compared to hires without AI pre-screening

Discover → Design → Develop

Process of Eiravox AI development company followed
to build the CV + Interview Video Analysis Platform:

Discover

Stakeholder Interviews

HRs, recruiters;

CEOs: pain points & desired outcomes.

Problem Framing

Manual CV screening inefficiencies;

Subjective interview evaluations;

Lack of structured insights for hiring decisions.

Market & Tech Research

Existing HR tech limitations;

API cost/performance (GPT, DeepSeek, Whisper, etc.);

Benchmarking Big Five, STAR, emotion detection models.

Design

Architecture Planning

Modular pipeline:

CV Parser → Interview Transcriber →
Analyzer → Report Generator;

Flexible input: video, transcript, resume.

ML/NLP Model Selection

Personality: Big Five via LLM prompt engineering;

Emotion: audio + video cues (optional);

STAR compliance: prompt templates + scoring logic;

CV skills: embedding + semantic matching.

UX/UI for HR Users

JSON & PDF output;

Visual dashboards;

Upload portals + API endpoints.

Develop

MVP Implementation

MCV analysis:

PDF/Docx parsing → skill/entity extraction;

Video ingestion → Whisper transcription → LLM analysis;

Prompt chains for each analysis stage.

Cost Optimization

DeepSeek for summarization/emotion scoring;

Local fallback models for budget use cases.

Cost Optimization

PDF report generation;

JSON API for integration with ATS/CRM;

Frontend dashboard (optional).

Deployment & Feedback Loop

Internal testing on mock interviews & CVs

Iterations with real client data;

Logging, debugging, prompt tuning.

AI integration partner

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