Inspiration

We were inspired by the difficulty many students and job seekers face when trying to understand how their CV translates into real job opportunities. Most users don’t know what skills they are missing or how to improve their profile to match industry expectations. We wanted to build an AI assistant that turns a simple CV into a clear and actionable career plan.

What it does

CareerAgent AI analyzes a user’s CV and provides:

Skill extraction and analysis Identification of strengths and weaknesses A personalized 3-month learning roadmap ATS-optimized CV generation LaTeX CV generation for professional use Job role suggestions based on the profile

How we built it

We built the project using Python and Streamlit for the frontend interface. The AI functionality is powered by the Google Gemini API. We designed a structured prompting system to ensure consistent outputs such as CV analysis, career planning, and job recommendations. We also added a fallback system to maintain functionality when the API is unavailable.

Challenges we ran into

One of the main challenges was dealing with API limitations such as rate limits and occasional service instability. Another challenge was ensuring that the AI output remains structured and useful instead of generating random or inconsistent responses. We solved this by refining prompt design and adding fallback logic.

Accomplishments that we're proud of

We are proud of building a full end-to-end AI career assistant that transforms raw CV data into structured career guidance. The system successfully integrates CV analysis, job matching, and resume optimization into one unified tool. We also implemented a resilient architecture that keeps the app functional even under API failures.

What we learned

We learned how to design and build AI agent systems, how to structure prompts for consistent outputs, and how to handle real-world issues like API failures and rate limits. We also gained experience in building user-focused AI applications rather than simple chatbots.

What's next for CareerAI

Next, we plan to:

Integrate real-time job scraping APIs (LinkedIn, Indeed, etc.) Add user accounts and CV history storage using MongoDB Enable PDF export for CVs Improve the AI agent to support multi-turn conversations Deploy a more scalable cloud version for wider usage

Built With

• gemini
• github
• google
• mongodb
• python
• streamlit
• studioai