JobHatch Enterprise

JobHatch Enterprise is an AI-powered HR tool that analyzes and ranks up to 5 resumes per job, offering smart matching, real-time cross-validation, and explainable insights—fully deployable end-to-end.

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Inspiration

Recruiters often waste hours sifting through resumes without clear insight into true candidate fit. We wanted to empower HR teams with an agentic, AI-powered solution that could evaluate, explain, and adapt—without requiring technical expertise or manual sorting.

What it does

JobHatch Enterprise is an all-in-one recruiting intelligence platform that empowers HR professionals to make faster, smarter hiring decisions. Recruiters upload a job description and up to 5 candidate resumes, and the AI agent automatically:

  • Extracts job intent using vector embeddings
  • Parses resumes to extract structured skills and experience
  • Ranks candidates based on vector similarity and LLM-generated match explanations
  • Cross-validates profiles with real-time web intelligence (LinkedIn, GitHub, portfolios, etc.)
  • Collects interviewer feedback to inform future recommendations
  • Learns team preferences over time to continuously improve matching accuracy

How we built it

Figma: Designed the frontend experience Next.js + Supabase: Resume and JD upload, feedback capture LlamaIndex + OpenAI Embedding: JD and resume vectorization Chroma: Vector database for candidate profiles ZeroEntropy: Feedback loop analysis Gemini 2.5 Flash: Multi-step reasoning and explanation (DeepMind) Arcade: Visual walkthrough demo for ToB showcase

Challenges we ran into

  • Parsing diverse PDF formats reliably

  • Balancing LLM latency with fast real-time scoring

  • Designing a scalable and interpretable feedback loop

Accomplishments that we're proud of

  • Built a fully working AI agent loop within 5 hours
  • Achieved interpretable candidate scoring with embedded GPT explanations
  • Delivered cross-validation capability with live internet signals
  • Created a ToB-ready deployment flow with UI/UX clarity

What we learned

-Agent-based architecture improves modularity in HR workflows

  • Combining vector search + LLMs makes HR evaluations powerful and explainable
  • Cross-validation builds trust in automated decision-making

What's next for JobHatch Enterprise

  • Scale resume handling: Expand the system to process 10 or more candidate resumes per job and support comparative matching across multiple job roles.
  • Enable talent mapping: Introduce a candidate mapping system that visualizes applicant strengths, gaps, and role fit across different departments or positions.
  • Pilot launch with partners: Deploy the platform with HR teams at partner companies during the upcoming fall recruitment season, collecting feedback to refine features and improve accuracy.

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