How We Created a Bot for Chess Players and Developed a Unique and Versatile MVP System

Task 🤔 A client approached us with a request for an MVP system for online chess players who stream their games on various platforms. The goal was to create a bot that tracks, monitors, and records streams, accessible through a subscription (SaaS).

Design 📋 Using the Lean Startup method, we started with the simplest MVP model, tested it in real conditions, analyzed the results, and refined the model. Only then did we move to the next stage. This method helped us avoid project delays and build a complex system from scratch in just 21 days.

Tools 🛠️ Briefly about the technologies and why we chose them:
✅ Python for development → AI integration
✅ Node.JS → handling requests and transmitting them to the user
✅ DynamoDB → NoSQL database
✅ Amazon S3 → storing screenshots and reports
✅ Django → optimizing the process of assembling all system elements
✅ YoLo → machine learning utility
✅ Grafana + Zabbix → data storage and visualization

Additionally, we used optical character recognition technology, PDF generation, and integrated necessary options for SaaS.

What Our Bot Can Do 🤖 The bot monitors streams, records game results, awards bonuses to players for winning, records the game, and stores the results in a database. It can then analyze this data, compare it with other combinations. Players can get a game report, analyze it, plan further moves (if the game is ongoing), or understand how to replay it. Each player has a profile to manage subscriptions, track game histories, and more.

Result 📍 The client was satisfied with the MVP system we created. The stack of tools and components we developed proved to be more effective than other options and versatile—successfully used for hundreds of other processes released into production.