Telegram app for learning Turkish
Turkish learning app LINGOBOTPopular Russian-language app with a growing user base and a powerful SEO strategy.
Viacheslav UstinovFullstack: Next.js, Zustand, FastAPI, Django, Postgre, Redis, Kafka
Popular Russian-language app with a growing user base and a powerful SEO strategy.
The app is built on a multi-layer architecture with clear separation between presentation, business logic, and data storage layers. The backend was initially developed on synchronous Django for a rapid service launch. As the user base grew to 2,500 active users, parts of the code are being incrementally rewritten in an asynchronous stack to boost performance and reduce scaling costs.
Component integration is handled via an aiogram-based Telegram bot and a Telegram Mini App built with Next.js. The bot manages commands and state, while the Mini App delivers a rich client-side interface and complex interaction logic.
As a result, users get access to:
The application’s frontend is built on Next.js, fully embracing Telegram authorization and the messenger’s native styling. The UI automatically adapts to the user’s Telegram settings (theme, fonts, controls). Implementing the Next.js + Telegram setup required tackling specific challenges—SSR constraints, routing nuances, secure handling of environment variables—not present in a pure React project. For a detailed walkthrough, code samples, and solutions, see my Medium article: https://medium.com/@ustsl/telegram-mini-applications-8a2602d6d4b8
A Next.js and Zustand site with a shared database, server-side rendering, and meticulous SEO, driving daily traffic to the Lingobot app.
If necessary, I can involve designers, data analysts, and senior-level developers in the project