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HireWise

🚀 Elevator Pitch

HireWise is an AI-powered resume screening tool that analyzes candidate resumes, matches them to job descriptions, and delivers smart hiring insights in seconds.

🌟 Inspiration

Hiring is time-consuming and screening hundreds of resumes manually is inefficient. We wanted to build a tool that empowers recruiters with instant, intelligent insights—saving time and making hiring smarter.

💼 What it does

• Uploads multiple resumes in PDF format
• Associates them with applicant IDs
• Uses AI (LLMs) to analyze resumes
• Allows querying candidate skills and qualifications
• Matches candidates against a job description
• Provides comparison tables and recommendations

🛠️ How we built it

• Frontend: Streamlit for interactive UI
  
• LLM: Groq's deepseek-r1-distill-qwen-32b model via LangChain
  
• Embeddings: SentenceTransformers (all-MiniLM-L6-v2)
  
• Vector Store: FAISS for semantic search
  
• PDF Parsing: LangChain’s PyPDFLoader
  
• Deployment Ready: Easily scalable and API key secured

🧱 Challenges we ran into

• Handling large PDF files with inconsistent formatting
• Aligning applicant IDs with resumes
• Embedding quality and performance tuning
• Ensuring results were human-readable and recruiter-friendly

🏆 Accomplishments that we're proud of

• Built a full working MVP with job matching, resume analysis, and candidate comparison
• Used open-source and cost-effective tools while keeping performance high
• Clean, responsive UI built with minimal effort using Streamlit

📚 What we learned

• Effective use of LLMs for RAG (Retrieval-Augmented Generation)
• Importance of structuring prompts and data for consistent results
• Balancing simplicity in UX with powerful backend logic

🔮 What's next for HireWise

• Add support for recruiter feedback loop and ratings
• Enable CSV export of comparison/match results
• Integrate ATS systems for end-to-end hiring workflows
• Include named entity recognition for better candidate summaries

Built With

• groq
• llms
• strreamlit