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align=\"center\"\u003e\n\n# Recruitment Copilot\n\n### AI-Assisted Recruitment Intelligence \u0026 Candidate Assessment\n\n![Python](https://img.shields.io/badge/Python-3.10+-blue?style=for-the-badge\\\u0026logo=python\\\u0026logoColor=white)\n![Streamlit](https://img.shields.io/badge/Streamlit-Dashboard-ff4b4b?style=for-the-badge\\\u0026logo=streamlit\\\u0026logoColor=white)\n![HR Tech](https://img.shields.io/badge/HR_Tech-Recruitment_Copilot-purple?style=for-the-badge)\n![Decision Support](https://img.shields.io/badge/AI-Human_Decision_Support-orange?style=for-the-badge)\n\nA recruiter-facing decision-support system that transforms candidate documents into structured hiring intelligence.\n\nThe repository includes a complete demonstration using a real AI \u0026 Data candidate profile, example recruiter briefing, and dashboard screenshots generated by the application.\n\nRecruitment Copilot compares CVs against job descriptions, extracts evidence signals, evaluates candidate fit, highlights strengths and verification points, and generates recruiter-ready interview briefings.\n\nDesigned as a transparent human-in-the-loop workflow rather than a black-box hiring system.\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"images/image-2.png\" width=\"850\"\u003e\n\u003c/p\u003e\n\n\u003c/div\u003e\n\n---\n\n## 🚧 Project Status\n\n\u003e **Work in Progress (MVP)**\n\u003e\n\u003e The current version uses deterministic skill matching and evidence extraction to demonstrate a complete recruitment decision-support workflow.\n\u003e\n\u003e Future versions will incorporate LLM-assisted analysis, richer document parsing, automation integrations, and multi-candidate workflow capabilities.\n\n---\n\n## Live Demonstration\n\nThe screenshots below demonstrate the system analyzing a real-world AI \u0026 Data candidate profile and generating a structured recruiter briefing.\n\n### Candidate Input\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"images/image-1.png\" width=\"550\"\u003e\n\u003c/p\u003e\n\nThe candidate CV and job description are provided to the system for analysis.\n\n---\n\n### Executive Assessment\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"images/image-2.png\" width=\"550\"\u003e\n\u003c/p\u003e\n\nThe system generates an overall recommendation, confidence level, and executive summary.\n\n---\n\n### Candidate Match Overview\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"images/image-3.png\" width=\"550\"\u003e\n\u003c/p\u003e\n\nTechnical fit, communication signals, portfolio evidence, and overall candidate alignment are evaluated.\n\n---\n\n### Evidence Signals\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"images/image-4.png\" width=\"550\"\u003e\n\u003c/p\u003e\n\nThe system identifies explicit skill matches and additional evidence categories including:\n\n* Communication \u0026 mentoring signals\n* Portfolio evidence\n* Certification evidence\n* Business \u0026 operational experience\n\n---\n\n### Evidence Highlights \u0026 Score Explanation\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"images/image-5.png\" width=\"550\"\u003e\n\u003c/p\u003e\n\nThe recruiter can inspect the reasoning behind the assessment through transparent score breakdowns and evidence highlights.\n\n---\n\n### Recruiter Briefing\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"images/image-6.png\" width=\"550\"\u003e\n\u003c/p\u003e\n\nA structured recruiter briefing is automatically generated to support interview preparation.\n\n---\n\n### Interview Preparation\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"images/image-7.png\" width=\"550\"\u003e\n\u003c/p\u003e\n\nSuggested interview questions are generated based on the detected evidence and candidate profile.\n\n---\n\n## 📄 Generated Recruiter Briefing\n\nA complete recruiter briefing generated from the example candidate analysis is included in this repository.\n\n➡️ **[View Generated Recruiter Briefing](outputs/sabrina_palis_recruiter_briefing%283%29.md)**\n\nThe demonstration uses a real AI \u0026 Data professional profile to showcase the system's evidence extraction, scoring, recommendation engine, and recruiter briefing capabilities.\n\nThe generated report includes:\n\n* Executive summary\n* Match assessment\n* Evidence highlights\n* Candidate strengths\n* Skills to verify\n* Interview preparation questions\n* Human review guidance\n\n---\n\n## Why This Project?\n\nRecruiters and hiring managers often review large numbers of applications under significant time pressure. Valuable information can be overlooked, while evaluation quality may vary between reviewers.\n\nRecruitment Copilot explores how AI-assisted workflows can help structure candidate information into consistent, explainable assessments without replacing human judgment.\n\nThe objective is not to automate hiring decisions.\n\nThe objective is to reduce administrative friction, improve review consistency, and help recruiters focus their time on higher-value conversations with candidates.\n\n---\n\n## 🔄 Operational Workflow\n\n```text\nCV + Job Description\n          │\n          ▼\nEvidence Extraction\n          │\n          ▼\nSkill Matching\n          │\n          ▼\nFit Assessment\n          │\n          ▼\nEvidence Verification\n          │\n          ▼\nInterview Preparation\n          │\n          ▼\nRecruiter Briefing\n```\n\nThe current MVP identifies:\n\n* Technical skill alignment\n* Experience signals\n* Communication and mentoring evidence\n* Portfolio and project evidence\n* Education and certification signals\n* Business and operational experience indicators\n\nAll outputs remain subject to human review.\n\n---\n\n## Features\n\n### Candidate Assessment\n\n* Upload or paste a CV\n* Upload or paste a job description\n* Automatic skill extraction\n* Technical fit scoring\n* Experience fit scoring\n* Education fit scoring\n* Communication evidence detection\n* Portfolio evidence detection\n\n### Evidence Analysis\n\n* Matched skills\n* Skills requiring verification\n* Partial or adjacent evidence\n* Teaching and mentoring signals\n* Certification signals\n* Business and operational signals\n\n### Recruiter Support\n\n* Executive summary\n* Recommendation tier\n* Evidence highlights\n* Transparent score breakdown\n* Interview preparation questions\n* Recruiter briefing generation\n* Markdown export\n\n---\n\n## Dashboard Components\n\nThe application currently includes:\n\n* Executive summary card\n* Recommendation card\n* Candidate match KPI cards\n* Match gauge visualization\n* Skill evidence section\n* Evidence signal detection\n* Top evidence highlights\n* Score explanation panel\n* Recruiter scorecard\n* Recruiter briefing report\n* Downloadable Markdown briefing\n\n---\n\n## Example Output\n\nThe system generates:\n\n* Overall match score\n* Recommendation level\n\nExamples:\n\n```text\nExceptional Match\nStrong Potential Fit\nPossible Fit\nPartial Fit\nWeak Fit\n```\n\nAnd produces a structured recruiter briefing including:\n\n* Executive summary\n* Candidate strengths\n* Skills to verify\n* Evidence highlights\n* Interview questions\n* Human review note\n\n---\n\n## 📁 Project Structure\n\n```text\nrecruitment-copilot/\n│\n├── app.py\n├── requirements.txt\n├── README.md\n├── .gitignore\n│\n├── sample_data/\n│   ├── sample_cv.txt\n│   └── sample_job_description.txt\n│\n├── src/\n│   ├── scoring.py\n│   ├── report_generator.py\n│   └── text_utils.py\n│\n├── images/\n│   ├── image-1.png\n│   ├── image-2.png\n│   ├── image-3.png\n│   ├── image-4.png\n│   ├── image-5.png\n│   ├── image-6.png\n│   └── image-7.png\n│\n└── outputs/\n```\n\n---\n\n##  Run Locally\n\nClone the repository:\n\n```bash\ngit clone https://github.com/YOUR-USERNAME/recruitment-copilot.git\ncd recruitment-copilot\n```\n\nCreate a virtual environment:\n\n```bash\npython -m venv .venv\n```\n\nWindows:\n\n```bash\n.venv\\Scripts\\activate\n```\n\nmacOS/Linux:\n\n```bash\nsource .venv/bin/activate\n```\n\nInstall dependencies:\n\n```bash\npip install -r requirements.txt\n```\n\nRun the application:\n\n```bash\nstreamlit run app.py\n```\n\nOr:\n\n```bash\npython -m streamlit run app.py\n```\n\n---\n\n## Current Scoring Logic\n\nThe MVP uses deterministic matching and evidence-based scoring.\n\nThe assessment currently combines:\n\n* Technical skill alignment\n* Experience indicators\n* Education and certification signals\n* Communication and mentoring evidence\n* Portfolio and project evidence\n\nThe goal is explainability rather than black-box prediction.\n\n---\n\n## ⚖️ Responsible AI Note\n\nRecruitment Copilot is a human decision-support prototype.\n\nIt is designed to:\n\n* Organize evidence\n* Support recruiter preparation\n* Improve review consistency\n* Reduce administrative workload\n\nIt is not designed to:\n\n* Automatically hire candidates\n* Automatically reject candidates\n* Replace recruiter judgment\n\nRecruitment decisions require human review, contextual understanding, fairness checks, and compliance with applicable employment law.\n\n---\n\n## Future Vision\n\nRecruitment Copilot is the first component of a broader exploration into AI-assisted operational systems.\n\nFuture versions will evolve from explainable screening toward recruiter workflow automation, candidate pipeline intelligence, and human-in-the-loop hiring support.\n\n---\n\n## Roadmap\n\n### Version 1.x — Explainable Screening\n\n* [x] Candidate/job matching\n* [x] Evidence extraction\n* [x] Recruiter briefing generation\n* [x] Skill evidence detection\n* [x] Communication evidence detection\n* [x] Portfolio evidence detection\n* [x] Explainable score breakdown\n\n### Version 2.x — AI-Assisted Analysis\n\n* [ ] LLM-powered CV extraction\n* [ ] Structured JSON outputs\n* [ ] Context-aware recruiter summaries\n* [ ] Dynamic interview question generation\n* [ ] Advanced evidence reasoning\n\n### Version 3.x — Recruitment Automation\n\n* [ ] Gmail integration\n* [ ] Airtable integration\n* [ ] Notion integration\n* [ ] Recruiter workflow automation\n* [ ] Candidate pipeline tracking\n* [ ] Multi-candidate ranking\n\n### Version 4.x — Agentic Recruitment Operations\n\n* [ ] Candidate sourcing workflows\n* [ ] Automated briefing generation\n* [ ] Hiring pipeline analytics\n* [ ] Recruiter copilot agent\n* [ ] Human-in-the-loop recruitment architecture\n\n---\n\n## 📜 License\n\nMIT License\n\n---\n\n### Built as part of a broader exploration of operational AI systems, human-in-the-loop decision support, workflow automation, and 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