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The recruitment process often involves manually reviewing numerous job descriptions (JDs) and CVs, which can be time-consuming and prone to human error. Job seekers often face the challenge of customizing their resumes to match specific job descriptions provided by different companies. Most resumes are generic and not aligned with the requirements mentioned in the job posting, resulting in poor ATS (Applicant Tracking System) scores and lower chances of being shortlisted. Manually tailoring each resume is time-consuming and inefficient, especially for candidates applying to multiple roles.
Agentic AI generates ATS-optimized resumes tailored to specific job descriptions of company that has opening. Users submit their details and job role, and the AI analyzes and matches their profile to the role, providing a custom resume, ATS score, and improvement suggestions. It also outputs a JSON resume and plans future auto-update integrations.
Technologies Used List the key technologies, frameworks, and tools you utilized in your solution Flask Streamlit Google Gemini API Gemini based on-prem LLMs LangChain Agentic AI frameworks:- Agno Flask-CORS Fitz
Challenges we ran into
Connection with database, llms, agentic ai agent. working with Agno Framework, Fitz, Searching for best llm agents,
To address the problem, we developed Agentic AI, an autonomous system that uses AI to analyze user-provided data—such as personal details, experience, certifications, and a specific job description. It applies NLP techniques to extract key requirements from the job post and maps them against the user’s profile. Based on this analysis, it generates an ATS-optimized resume tailored for that role, calculates an ATS score, and provides actionable suggestions (e.g., relevant projects, skills). The system outputs a structured JSON format of the resume. Future enhancements include GitHub and email integration for real-time resume updates and interview alerts.
User submits personal information, experience, certifications, and a specific job description from a company.
A personalized, ATS-optimized resume is generated using intelligent prompt chaining and agentic reasoning techniques.
The system provides an ATS score and actionable insights (skills, certifications, projects) to improve job alignment.
Resume is exported in JSON format, with future automation planned via GitHub and email integrations for continuous updates.
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