🧠 WeaveIQ

Deployed Link: https://weave-net-two.vercel.app/

An AI-powered talent intelligence engine that goes beyond resumes to uncover hidden potential using skill relationships and explainable matching.

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💡 Solution

WeaveIQ introduces a skill-driven intelligence layer that:

• Extracts capabilities from raw data (resume / GitHub)
• Builds relationships between skills using a graph-based model
• Identifies adjacent (transferable) skills
• Matches candidates to roles intelligently
• Provides explainable recommendations

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⚙️ How It Works

Input (Resume / GitHub)
        ↓
Skill Extraction
        ↓
Skill Graph (Relationships)
        ↓
Adjacency Detection
        ↓
Matching + Scoring
        ↓
Explainable Output

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🔥 Key Features

• 🧠 Skill Extraction Engine Extracts capabilities from unstructured text

• 🔗 Skill Graph Intelligence Models relationships between skills

• 🔥 Adjacency Engine (Core USP) Detects near-fit candidates via related skills

• 📊 Scoring System Combines direct and adjacent matches

• 🧾 Explainability Layer Transparent reasoning behind every decision

• 🌐 API Layer Enables seamless frontend integration

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🧰 Tech Stack

• Backend: Node.js, Express
• AI/ML : Hugging Face Embeddings
• Graph Logic: Neo4j-ready
• APIs: RESTful endpoints

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🚀 Getting Started

1. Clone the repository

git clone https://github.com/harleen05/weaveNet.git
cd weaveNet/server

2. Setup environment variables

cp .env.example .env

3. Install dependencies

npm install

4. Run the server

npm run dev

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📥 Example Input

{
  "candidate_text": "Experience in React, JavaScript and Express",
  "role_skills": ["Node.js", "MongoDB", "React"]
}

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📤 Example Output

{
  "score": 75,
  "matched": ["React"],
  "adjacent": ["Node.js"],
  "missing": ["MongoDB"],
  "explanation": "Strong frontend skills with some backend exposure. Missing database experience."
}

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