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Recruiter+

Client

Recruiter+

Duration

Ongoing

Year

2025

#AI / Machine Learning#RAG#HR Tech

Recruiter+

AI-Powered Hiring Assistant

Recruiter+ transformed hiring from a gut-feel, manual slog into a fast, evidence-based operation — with semantic search, live candidate intelligence, and AI recommendations every recruiter can explain and defend.

Challenges

A Manual, Disconnected Hiring Process

Manual CV Screening

Recruiters manually read hundreds of CVs — time-intensive, inconsistent, and prone to missing great candidates

Poor Search Quality

Keyword-based filtering misses semantically relevant candidates and over-returns irrelevant ones

No LinkedIn Integration

Candidate profiles go stale instantly; no live signal on current role, skills, or activity

Zero Explainability

Shortlisted candidates had no rationale — recruiter couldn't justify or audit the recommendation

No Scale Path

Processing 10,000+ CVs was cost-prohibitive and beyond API rate limits with standard pipelines

Fragmented Data Sources

CV data, metadata, and LinkedIn profiles stored separately with no unified candidate identity

Project visual

Solution

End-to-End AI Hiring Pipeline Built for Scale & Explainability

Technovate Global designed and deployed a fully integrated RAG-powered hiring platform — from CV ingestion and LinkedIn enrichment to semantic retrieval and explainable AI recommendations.

1

Intelligent CV Ingestion

LlamaParse + GPT-4o-mini

Parses complex PDF layouts into clean Markdown; LLM extracts structured JSON metadata — zero manual entry

2

Dual-Database Engine

PostgreSQL + Qdrant Cloud

Relational master store for identity & full text; vector index for semantic search with metadata prefiltering

3

Automated LinkedIn Enrichment

Apify Scraping API

Background scraping triggered on upload; live re-scrape on shortlist or profile view; auto-refresh every 6 months

4

RAG Retrieval Pipeline

OpenAI Embeddings + Qdrant

Natural language queries translated to metadata filters; oversampling + deduplication guarantees 5 unique candidates

5

Explainable AI Recommendations

GPT-4o Synthesizer

Every recommendation cites the exact CV line or LinkedIn section that justifies the claim — fully auditable

6

Batch Processing Engine

OpenAI Batch API + AWS SQS

Processes 10,000+ CVs in background batches of 500; cuts LLM token costs by 50% and bypasses rate limits

Transformation

Before vs. After

Before
After

Manual CV reading for every role

AI-parsed, fully searchable candidate database

Keyword filtering missing top talent

Semantic vector search finds best semantic matches

Stale candidate profiles

Live LinkedIn enrichment on shortlist & auto-refresh

No justification for shortlists

Every recommendation cites exact CV/LinkedIn evidence

Batch imports crashing rate limits

50% cheaper batch pipeline handling 10,000+ CVs

Fragmented candidate identity

Unified candidate_id across all CVs, versions & profiles

Results

The Numbers Speak

0%

Reduction in LLM extraction costs via Batch API

<1s

Semantic candidate retrieval at query time

0+

CVs processable in a single background batch

0%

Recommendations backed by cited CV/LinkedIn evidence

Technology

Stack at a Glance

Document Parsing

LlamaParse (complex PDF → Markdown)

Intelligence & Extraction

OpenAI GPT-4o-mini + Batch API (structured JSON, 50% cost reduction)

Embeddings

OpenAI text-embedding-3-small

Vector Index

Qdrant Cloud (metadata prefiltering)

Relational Store

PostgreSQL (entity resolution, full-text storage)

LinkedIn Enrichment

Apify (managed proxy scraping)

Infrastructure

AWS S3, SQS, Lambda/EC2 (async processing)

Outcome

What Recruiter+ Gained

Recruiter+ transformed hiring from a gut-feel, manual slog into a fast, evidence-based operation — with semantic search, live candidate intelligence, and AI recommendations every recruiter can explain and defend.

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