AI-Based Resume Matcher & Intent Search
Budget: ₹75,000 – ₹150,000 INR
Project Requirement: Build AI Resume Matching System with Intent-based Search (Up to 10,000 Resumes)
Project Overview:
We are building an AI-powered Resume Matching Platform that can handle up to 10,000 resumes initially.
The platform should perform semantic search, intent extraction from job descriptions, and intelligent matching of resumes based on meaning, not just keywords.
The system should be multi-tenant — allowing multiple recruiters to use it separately.
Key Features:
Resume Upload & Parsing
Allow bulk upload of resumes (PDF, Word, Text files).
Parse resumes into structured JSON (Name, Skills, Experience, Education, Certifications).
Vector Embedding
Generate semantic vector embeddings for each resume and job description using OpenAI or Cohere API.
Store embeddings in a scalable vector database (Pinecone, Weaviate, or ChromaDB).
Intent Extraction
Analyze uploaded job descriptions.
Extract the job intent — main skills, role type, experience level, domain, etc. using GPT-4 Turbo or similar LLM.
Semantic Search + Intent Matching
Match and rank resumes based on semantic relevance and intent alignment with the JD.
Result should show: Top Match, Good Fit, Average Fit categories.
Multi-Tenant Recruiter Portal
Create accounts for different recruiters (each recruiter sees only their own resumes and JDs).
Simple, clean dashboard for uploading resumes, job descriptions, and viewing matches.
Hosting & Scalability
Host the system on AWS, Render, Railway, or any scalable cloud platform.
Ability to easily upgrade capacity if resume count increases later.
Automation Features (Optional for Phase 2)
Email or WhatsApp automation for sharing JD matches with candidates.
Technical Requirements:
Backend: Python (FastAPI preferred) or Node.js
Frontend: React.js or Streamlit (for fast development)
Database: MongoDB, Firebase, or PostgreSQL
Vector Database: Pinecone / ChromaDB (or suggest better)
LLM: OpenAI GPT-4 Turbo API (or similar)
Authentication: JWT or OAuth2
Deliverables:
Fully working system (Backend + Frontend)
API Documentation
Admin panel for monitoring usage
Deployment instructions
Source code with proper commenting
Project Overview:
We are building an AI-powered Resume Matching Platform that can handle up to 10,000 resumes initially.
The platform should perform semantic search, intent extraction from job descriptions, and intelligent matching of resumes based on meaning, not just keywords.
The system should be multi-tenant — allowing multiple recruiters to use it separately.
Key Features:
Resume Upload & Parsing
Allow bulk upload of resumes (PDF, Word, Text files).
Parse resumes into structured JSON (Name, Skills, Experience, Education, Certifications).
Vector Embedding
Generate semantic vector embeddings for each resume and job description using OpenAI or Cohere API.
Store embeddings in a scalable vector database (Pinecone, Weaviate, or ChromaDB).
Intent Extraction
Analyze uploaded job descriptions.
Extract the job intent — main skills, role type, experience level, domain, etc. using GPT-4 Turbo or similar LLM.
Semantic Search + Intent Matching
Match and rank resumes based on semantic relevance and intent alignment with the JD.
Result should show: Top Match, Good Fit, Average Fit categories.
Multi-Tenant Recruiter Portal
Create accounts for different recruiters (each recruiter sees only their own resumes and JDs).
Simple, clean dashboard for uploading resumes, job descriptions, and viewing matches.
Hosting & Scalability
Host the system on AWS, Render, Railway, or any scalable cloud platform.
Ability to easily upgrade capacity if resume count increases later.
Automation Features (Optional for Phase 2)
Email or WhatsApp automation for sharing JD matches with candidates.
Technical Requirements:
Backend: Python (FastAPI preferred) or Node.js
Frontend: React.js or Streamlit (for fast development)
Database: MongoDB, Firebase, or PostgreSQL
Vector Database: Pinecone / ChromaDB (or suggest better)
LLM: OpenAI GPT-4 Turbo API (or similar)
Authentication: JWT or OAuth2
Deliverables:
Fully working system (Backend + Frontend)
API Documentation
Admin panel for monitoring usage
Deployment instructions
Source code with proper commenting