Alignify

Finishing up the frontend
checking on our dear friend 'Git'
Setting up the backend
Putting in sample 'bad' resumes and testing the working
Zzzz...
Signing off from the hackathon – until next time!

Inspiration

We were inspired by the real struggles job seekers face—especially when their resumes are filtered out by automated Applicant Tracking Systems (ATS). Many talented professionals possess exceptional skills and experiences but fail to secure interviews because their resumes aren’t optimized for modern screening tools. This challenge motivated us to create Alignify, an AI-powered ATS Resume Reviewer that empowers users to transform their resumes into career-winning documents.

What it does

Alignify analyzes resumes in the context of specific job descriptions. By comparing a user’s resume against a targeted job posting, our platform:

Assigns an ATS compatibility score. Identifies missing keywords and areas that need improvement. Provides detailed, actionable suggestions on what to change and how to enhance the resume. Stores each analysis for users to review later via a personalized dashboard.

How we built it

We built Alignify using a modern full‑stack approach:

Frontend: Developed with React and styled with Tailwind CSS. We integrated Auth0 for secure user authentication, allowing users to log in and access their personalized dashboard. Backend: Constructed using Node.js and Express. Our backend handles file uploads with Multer and extracts text from PDFs using pdf-parse. We then call the OpenAI ChatGPT API (via a custom prompt) to generate tailored feedback. The analysis is saved in MongoDB using Mongoose. Database: MongoDB stores each analysis along with the user’s resume, job description, and Auth0 user ID, enabling personalized history tracking. AI Integration: We crafted detailed prompts to instruct ChatGPT to review resumes line-by-line and return structured, actionable feedback on the conceptual lines of agentic AI.

Challenges we ran into

Prompt Engineering: Refining the prompts to get clear, structured output from ChatGPT was a significant challenge. File Parsing: Handling different resume formats (especially PDFs) and ensuring accurate text extraction required iterative improvements. API Integration: Managing the asynchronous API calls, error handling, and ensuring the output was correctly parsed and stored. Deployment & Security: Transitioning from local development to a cloud-hosted environment while safeguarding sensitive API keys and user data posed additional hurdles.

Accomplishments that we're proud of

Successfully integrating cutting-edge AI to deliver personalized resume analysis. Creating a seamless user experience from login through analysis submission and historical data review. Implementing a full‑stack solution that securely stores user data and provides actionable feedback. Overcoming technical challenges related to file parsing and prompt optimization.

What we learned

We learned valuable lessons across multiple areas:

AI and Prompt Engineering: How to effectively communicate with the OpenAI API and refine prompts to yield structured and useful output. Full-Stack Development: Best practices in integrating a React frontend with a Node.js/Express backend, along with secure user authentication via Auth0. Database Management: How to design and implement a scalable data storage solution using MongoDB and Mongoose. Collaboration & Problem-Solving: The importance of iterative testing, teamwork, and agile development in overcoming complex challenges.

What's next for Alignify

Looking ahead, we plan to:

Enhance User Personalization: Integrate additional user analytics and recommendations based on historical data. Improve AI Output: Continue refining our prompts and integrating newer AI models as they become available. Expand Feature Set: Add more resume optimization tools and expand our dashboard with deeper insights. Scalability and Integration: Explore partnerships with career platforms and integrate with popular job boards to provide real-time market insights. Security Enhancements: Implement full backend JWT verification for tighter security and improved user data protection.