Projects/AI Platforms/hAIre – AI Hiring Suite
Case Study

hAIre – AI Hiring Suite

Faster, fairer hiring decisions.

A modular hiring system powered by large language models to streamline recruitment, reduce bias and support better decisions.

Industry
HR & Recruitment
Status
Phases 1–2 live: CV screening in daily use, interview engine ready to deploy
Timeline
1404 (SH)
Partners
Built for FANAP's HR recruitment team
hAIre – AI Hiring Suite
HIRE WITH
CONFIDENCE
01 / The Problem

Hiring is slow, manual and biased.

Recruiters spend hours screening CVs, interviews are inconsistent and unconscious bias shapes decisions.

Hours of manual CV screening
Inconsistent interview evaluation
Unconscious bias in decisions
Scattered notes and reports
Structured evaluation
Structured
evaluation
02 / Our Solution

Three modules, one hiring flow.

hAIre covers the full journey: CV screening with fit scoring and red-flag detection, an interview co-pilot with bias alerts and reports, and an AI interviewer for one-way and live sessions.

Technical details
Shahab – CV Screening
Shahab – CV Screening
Structured extraction, fit score, red flags and duplicate detection
Nahid – Interview Co-pilot
Nahid – Interview Co-pilot
Real-time bias alerts, scorecards and post-interview reports
Bahram – AI Interviewer
Bahram – AI Interviewer
Adaptive live interviews with transcripts and evaluations
03 / System Architecture

API-first and privacy-aware.

Integrates with existing ATS and meeting tools.

CVs & Jobs
(Input)
LLM Engine
(Parsing & scoring)
Interviews
(Co-pilot & AI interviewer)
Reports
(PDF / JSON)
04 / Technical Details

Inside the three modules.

Shahab – CV screening intelligence
  • LLM-based structured extraction of skills, experience, education and more
  • Dual-mode fit score (structured + black-box evaluation)
  • Red-flag detection: job hopping, gaps, vague roles
  • Duplicate resume detection using embeddings
Nahid – interview assistant for hiring managers
  • Real-time bias alerts, e.g. halo effect and confirmation bias
  • Dynamic scorecard with auto-saving and rating
  • Detailed post-interview reports: strengths, concerns, fit
  • Zoom / Meet integration with markdown-friendly note-taking
Bahram – AI-powered interviewer
  • One-way and two-way interview modes (via LiveKit)
  • Adaptive questions, follow-ups and real-time scoring
  • Auto-generated PDF / JSON reports with transcripts and evaluations
  • Smooth live audio with under 700 ms latency
Key features
  • Resume parsing and semantic fit scoring
  • Interview automation and reporting
  • Real-time bias and anomaly detection
  • API-first, secure and privacy-aware
The four-phase funnel
  • Smart CV screening against the exact job ad (live as a Chrome extension)
  • Tailored interview path built from each candidate's resume
  • Automated verification of resume claims
  • Comparison and recommendation with clear reasons
05 / Results

Performance.

3
Integrated modules
<700 ms
Live interview audio latency
200/day
CVs & interviews in cost model
06 / The Team

The people behind it.

A multidisciplinary team of engineers, researchers and domain experts.

Rozhina Taghdimi
Rozhina Taghdimi
Machine Learning Engineer
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Ilia Forsati
hAIre Team
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Seyed Mohammad Javad Feyzabadi Sani
hAIre Team
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Reyhaneh Alavi
hAIre Team
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Ghazaleh Fathi
hAIre Team
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Ali Nabipour
hAIre Team
07 / Gallery

More from this project.

Visuals of the system and its components.

Candidate pipeline
Interview design assistant
Candidate evaluation
Interview validation report
Full interview transcript
08 / What's Next

Scaling for broader impact.

We are expanding hAIre with more languages, job families and ATS integrations.

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