AI-Powered Peer Voting Platform
Flashrank is a unique web-based platform where users can determine their best photos using peer voting, driven by the Elo ranking model. The system dynamically adjusts photo rankings as more users vote in head-to-head matchups, offering a gamified and intelligent photo evaluation experience.
What is Flashrank?
Flashrank helps users choose their best photos through intelligent peer-based voting.
Users upload multiple images and share a private link for friends or followers to vote. The system intelligently compares photos in pairs and ranks them using a statistical model derived from chess - the Elo rating system.
Industry
Others
Services We Provided
Web Development, Web Hosting Solutions
Project Duration
1 Months
Technologies We Use
React
Material-UI
Styled Component
SCSS
Node.js
PostgreSQL
TypeScript
The ChallengeIntelligent Voting System
How do you rank photos fairly and quickly using peer votes?
Traditional voting systems either offer simple likes or percentage-based polls. We wanted a more nuanced, statistically fair method of comparison using pairwise matchups. The challenge was to implement this at scale while ensuring a real-time experience for users.
Building a fair ranking model using Elo
Ensuring seamless voting experience through efficient pairing
Handling high concurrency during viral shares
Maintaining vote integrity and preventing misuse
Our SolutionBuilding Flashrank
The project was broken down into key milestones - from idea to real-time MVP.
Architecture & Planning
Defined feature scope, user interactions, and technical requirements. Designed a modular system architecture optimized for image-based comparison workflows and scalable growth.
Backend Engineering
Implemented a Node.js backend with PostgreSQL for persistent storage and accurate Elo-based scoring logic. Built endpoints to handle submissions, pairings, and ranked results with data consistency in mind.
Frontend Development
Developed a responsive interface using React, Material UI, and Styled-Components. Emphasis was placed on accessibility, ease of use, and a frictionless voting experience across devices.
Testing & Deployment
Conducted functional and usability testing to ensure ranking accuracy and voting flows worked as intended. The platform was deployed via a cloud-managed infrastructure using Node.js and PostgreSQL.
