Telegram Bots & Media Cases

Overview

The bot is integrated with iCafeCloud and gives users quick access to balance, session and available seats right from Telegram. It automates routine admin work and improves the service experience for club guests.

Implemented Features

• User authentication and secure session without storing sensitive data in the bot.
• Account area: profile, balance, bonus account and account status.
• Active session monitoring: PC, gaming zone, duration and time left.
• Live seat availability grouped by zone with occupancy stats.
• Extensible architecture for booking, payments, orders and tournament modules.

Tech Stack

• Telegram Bot API with asynchronous server logic.
• iCafeCloud integration via REST API.
• Scaling support for a club network and growing load.

Result

The club gains a round-the-clock self-service channel for clients, while the team sees fewer manual requests and a faster operational cycle.

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Overview

A support bot where users write in a private chat and managers reply from a separate work chat. The bot stores history, supports photos and documents, and sends the reply to the user anonymously on behalf of support.

Architecture

• Python + python-telegram-bot (async mode).
• PostgreSQL with a connection pool (psycopg2.pool).
• Tables: users, messages, active_replies.
• File and console logging for audit and diagnostics.

Key Functionality

• Message routing: text, photos and documents are forwarded to the manager chat automatically.
• Inline buttons for managers: "Reply to user" and "Message history".
• Active reply state: a manager answers a specific dialog, then the state is cleared.
• Anonymous replies: the user gets a message from support without the manager identity.
• History and reports: conversation storage and delivery reports.
• Manager commands: cancel current reply and usage instructions.
• Error handling: blocked bot, unreachable chat, fallback behaviour.

Result

Support gained a single managed communication channel, transparent request history and a faster response cycle for clients.

Note: configuration secrets (tokens, passwords, private identifiers) are hidden and not published.

What we did

• Audience segmentation by activity and visit frequency.
• Campaign templates and automated campaigns.
• A/B message scenarios and response analytics.

Result

Higher user return rate and a larger share of clients responding to special offers.

What we did

• Connected media screens to a centralised content source.
• Synced schedule, promos and live metrics in real time.
• Added fallback display scenarios for connection loss.

Result

Screen content became current and manageable without manual updates.