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:
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.





