Projects using FastAPI in DelhiProjects using FastAPI in DelhiAI Resume Screening | Candidate Ranking System | AI HR Recruiter | ATS CV/Resume Optimization
𝗢𝘃𝗲𝗿𝘃𝗶𝗲𝘄
Recruiters often spend hours manually reviewing resumes, comparing candidate qualifications, and identifying the best fit for open positions. To address this challenge, I developed an AI-powered Resume Screening and Candidate Ranking Platform that automates candidate evaluation, improves hiring efficiency, and reduces recruitment time.
𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲
Traditional recruitment processes involve reviewing hundreds of resumes for a single position. This manual approach is time-consuming, inconsistent, and often results in qualified candidates being overlooked. Recruiters needed a solution capable of quickly analyzing resumes, matching them against job requirements, and generating reliable candidate rankings.
𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻
I built an intelligent recruitment platform that leverages Artificial Intelligence and Natural Language Processing (NLP) to automate resume analysis and candidate assessment.
𝗞𝗲𝘆 𝗳𝗲𝗮𝘁𝘂𝗿𝗲𝘀 𝗶𝗻𝗰𝗹𝘂𝗱𝗲:
- ATS-compatible resume parsing for PDF and DOCX files
- Automated extraction of skills, experience, education, certifications, and contact information
- AI candidate matching based on job descriptions
- Intelligent candidate scoring and ranking system
- Semantic skill matching using NLP techniques
- Automated shortlist generation for recruiters
- Recruiter dashboard for managing applications and rankings
- Bulk resume processing for high-volume recruitment
- Interview recommendation system based on candidate fit
- Fair and consistent evaluation framework to reduce manual bias
𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗣𝗿𝗼𝗰𝗲𝘀𝘀
The platform was designed with scalability and accuracy in mind. The workflow begins by parsing uploaded resumes and extracting structured candidate data. AI models then compare candidate profiles against job requirements, analyzing technical skills, years of experience, educational background, and industry relevance.
A ranking engine generates compatibility scores and presents candidates in order of suitability. Recruiters can review detailed scoring insights, compare applicants, and make faster hiring decisions.
𝗥𝗲𝘀𝘂𝗹𝘁𝘀
The solution significantly improved recruitment efficiency and candidate discovery.
𝗢𝘂𝘁𝗰𝗼𝗺𝗲𝘀
> Reduced manual resume screening time by up to 80%
> Accelerated candidate shortlisting process
> Improved recruiter productivity and hiring speed
> Increased consistency in candidate evaluation
> Enabled processing of hundreds of resumes within minutes
> Enhanced talent identification through AI-driven matching
𝗖𝗼𝗻𝗰𝗹𝘂𝘀𝗶𝗼𝗻
This AI recruitment platform transforms traditional hiring workflows by automating resume screening, ranking candidates intelligently, and helping recruiters identify top talent faster, more accurately, and at scale. I built a professional, end-to-end AI Receptionist system designed to automate clinic appointment management. This isn't just a chatbot; it's an AI Agent that can reason, use tools, and manage a live database autonomously.
Key Contributions:
Agentic Reasoning: Integrated CrewAI with Llama 3.3 (Groq) to enable the agent to understand complex user intents (Booking vs. Cancellation) and relative time (e.g., "next Tuesday at 3pm").
Autonomous Tool Use: Developed custom Python tools that allow the agent to verify real-time availability in a SQLite database and execute atomic transactions without human intervention.
High-Performance Backend: Built a robust API using FastAPI to handle asynchronous requests between the AI agent and the database.
Premium Dashboard: Designed a modern, Glassmorphic UI using Tailwind CSS that provides a real-time sync of the clinic’s schedule.
The Result:
A seamless, hands-free system that reduces administrative overhead by 100%, allowing clinic staff to focus on patients while the AI handles the entire scheduling lifecycle.
Tech Stack:
Python, CrewAI, Groq API, FastAPI, SQLite, Tailwind CSS
