DEV Community: AMAN RAJ

Building the future of fan engagement for FIFA 2026! ⚽️🤖

AMAN RAJ — Tue, 21 Jul 2026 01:52:27 +0000

I’m thrilled to share that I’ve just deployed my latest project, ArenaGPT, a concierge application designed to enhance the experience for the FIFA 2026 tournament!

Developing this project was an intense but incredibly rewarding journey. My goal was to create a smart, efficient, and user-friendly tool that provides real-time stadium information and support to tournament fans.

Key highlights of the project:

Tech Stack: Built with Streamlit for a fast, responsive UI and powered by Google Gemini 3.5 Flash for intelligent backend responses.

Data & Mapping: Utilized Pandas to structure the coordinate data for all 16 host stadiums, allowing for dynamic, interactive venue mapping within the app.

Engineering Focus: Prioritized security from day one by implementing environment-based secret management, ensuring sensitive API keys remain protected and out of public version control.

Deployment: Successfully moved from local development to production using GitHub and Streamlit Community Cloud.

This project was a great opportunity to dive deeper into Python, improve my Git workflows, and apply AI to a real-world sporting event.

🎯 How to Use ArenaGPT

ArenaGPT is designed to be a simple, intuitive concierge. Here is a quick guide to its core features:

1. Select Your Stadium

Purpose: To tell the AI which venue you are interested in so it can provide specific, relevant information.

How it works: Click on the dropdown menu labeled "Select your stadium:".

Scroll through the list and choose one of the 16 official FIFA 2026 host stadiums (e.g., MetLife Stadium, AT&T Stadium).

The app will instantly update the map and the AI assistant's instructions to focus on that specific location.

2. Interactive Venue Map

Purpose: To provide a visual reference of the stadium's location and its surroundings.

How it works: Once you select a stadium, a map will appear below the dropdown.

Use your mouse or touchpad to pan (click and drag) and zoom (scroll wheel or +/- buttons) to explore the area.

A red location pin marks the exact spot of the stadium.

3. AI Concierge (Chat Interface)

Purpose: To get instant answers to your questions about the stadium, match day operations, and tournament rules.

How it works: Locate the chat input box at the bottom of the page, which reads "Ask ArenaGPT about [Your Selected Stadium]...".

Type your question clearly. For example:

Press Enter or click the arrow icon to send your message.

The AI will process your request and provide an answer based on its current database of FIFA 2026 information.

Check out the project here: https://arenagpt.streamlit.app/

I’d love to hear your thoughts or feedback! Always looking to connect with others interested in AI, software development, and the future of sports technology.

From Classroom to Code: My Journey as a Student Developer

AMAN RAJ — Sat, 18 Jul 2026 19:22:49 +0000

The path to becoming a software developer isn't always a straight line. For me, it has been a journey defined by curiosity, the challenge of balancing university academics with hands-on projects, and the thrill of seeing code come to life. As a BCA student at Cimage Professional College(AKU) Patna, I’ve learned that the most important lessons often happen outside the lecture hall—right where the keyboard meets the screen.

Why I Choose to Build

For many, a stressful day might call for a getaway or a break. For me, the best remedy is a coding project. Whether I’m navigating the complexities of Python or diving into the performance-focused world of Go, I’ve found that building something tangible—even when it’s difficult—is the most rewarding way to learn.

My current focus has been an ambitious cross-device AI agent. The goal? To create a seamless experience where an agent can be controlled from a laptop while running tasks across mobile platforms (Android and iOS). It’s been an intense process of debugging, architecture planning, and constant iteration, but it’s precisely these "tough" projects that have taught me more than any textbook could.

Balancing Act: Exams and Innovation

Being a student means navigating a rigorous academic schedule. I’ve recently finished my first-semester backlog exams, which served as a good reminder of the discipline required to balance theory with my passion for software development.

However, the goal is always looking forward to graduation in 2028. Every milestone, whether it's passing a math exam or successfully deploying a feature in my AI agent project, feels like a step toward building a real impact in the tech space.

Getting Out into the Community

I believe that technical growth doesn't happen in a vacuum. That’s why I’ve been actively participating in the local tech scene here in Bihar. Recently, I registered for the Bihar AI Summit 2026. Engaging with the community, learning from peers, and staying updated with the latest AI trends is a huge part of how I plan to grow my career.

What’s Next?

My journey is still in the early stages, but I am excited about where it’s heading. Whether I am deep-diving into Go concurrency models or brainstorming new features for my AI agent, I’m committed to the process of continuous improvement.

If you’re a student developer or someone who finds peace in solving complex problems, let’s connect! I’d love to hear what projects you’re currently working on or how you handle the balancing act between university and personal development.

Happy coding!

Graphing the Future: How We Built HealthCurve Nova AI for HackHazards 2026 🚀

AMAN RAJ — Tue, 02 Jun 2026 01:12:04 +0000

Graphing the Future: How We Built Health Curve Nova AI for HackHazards 2026 🚀

Balancing my BCA coursework while diving into a massive buildathon is always a rush. HACKHAZARDS '26 runs as a two-month event from May to June 2026, giving us the time and space to ship a production-grade project instead of just a rushed prototype. With an incredible line-up of sponsors and a global pool of builders, my team and I set out to build Health Curve Nova AI.

Here is a look into our development journey, the challenges we tackled, and the tech that made it possible.

🛑 The Problem We Solved

Managing multiple prescriptions, understanding dosages, and maintaining a strict medication schedule is a daily struggle for millions, particularly the elderly. Missed or incorrect doses can lead to severe complications.

Health Curve Nova AI solves this through a dynamic OCR-based medication scheduling system. By simply snapping a picture of a medical prescription, our application uses AI to read the text, extract the medication details, and automatically generate a dynamic, conflict-free schedule for the patient.

🛠️ Our Tech Stack

To build a scalable and responsive application, we utilized a mix of powerful frameworks and tools:

**Frontend: Netlify (Vanilla JavaScript) – Enabled us to deploy a lightweight, fast, and cross‑platform web interface without relying on React Native.
Backend: Python (Flask) & Render Workflows – We needed a highly performant backend to handle our core OCR logic, and we utilized Render Workflows to manage our automated AI agent routing and API endpoints.
Database: Neo4j – The backbone of our data architecture, allowing us to map complex relationships between patients, medications, and time intervals.
Deployment & DevOps: Render – For robust hosting, continuous deployment, and managing our background systems.

🤝 Partner Tracks Used

We specifically targeted the partner tracks provided by the hackathon sponsors to elevate our project. The hackathon is structured around core technology pillars, and we made sure to utilize them effectively:

The Neo4j Track: Traditional relational databases wouldn't cut it for our highly connected data. We leveraged Neo4j's graph database capabilities via AuraDB to map complex medication schedules and check for potential drug interaction nodes.
The Render Workflows Track: Managing an automated OCR pipeline and AI scheduling requires a resilient backend. We used this track to build and deploy durable AI agents that reliably orchestrate the flow of data between the user's camera, the processing engine, and the graph database.

⚙️ Implementation & Architecture

Our architecture follows a straightforward but powerful flow:

The user takes a photo via the Expo frontend, which sends the image to our Flask backend.
The backend, operating as a durable agent on Render, triggers our AI/OCR pipeline to parse the messy prescription text into structured JSON data.
From there, the backend constructs Cypher queries to interact with the Neo4j database. It checks for existing prescriptions, maps the new schedule, and flags any overlapping contraindications.
Finally, the processed schedule is pushed back to the frontend, which sets up local push notifications for the user.

🧗 Challenges Faced

No hackathon is complete without a few late-night debugging marathons.

Taming the AI: Getting the OCR model to accurately read varying handwriting styles from doctors required extensive prompting and fallback logic.
Connecting the Graph: Wrapping our heads around Cypher queries and optimizing them for our Flask backend took some trial and error. My teammate, Aditya Raj, and I spent hours debugging our graph schemas to ensure the edge relationships between different drugs were mapped correctly.
State Management: Managing complex state across our Expo application while ensuring the UI remained snappy required several refactors.

🎉 Conclusion

Building Health Curve Nova AI for HackHazards 2026 pushed us to explore new architectural patterns, heavily utilize AI agents, and leverage graph databases in ways we hadn't before. It was a massive step up from a standard 24-hour sprint.

A massive thank you to the sponsors for the tools, and a special shoutout to the organizers for putting together such an incredible platform and event! If you want a deeper behind-the-scenes look at the code and our development process, be sure to check out the devlog series on my YouTube channel, AmanCodeLogs.

Let me know your thoughts on our approach in the comments below! 👇