Developed an advanced AI assistant based on n8n, which provides 24/7 automation of service bookings for a barbershop.
Technical implementation:
Integration of LLM via MCP: Connecting ChatGPT using Model Context Protocol for dynamic interaction with the backend (NocoDB, Airtable, Supabase, Google Sheets). The assistant autonomously queries current prices, services, and available time slots of masters.
Smart memory: Utilizing Supabase (PostgreSQL) to store long-term context — the bot remembers details of previous conversations with clients.
Omnichannel: Connecting the bot to the most popular communication platforms (WhatsApp, Telegram, Web Chat).
Schedule synchronization: Direct integration of scheduling systems (Google Calendar) and CRM.
Business outcome:
Saving over 80 hours a month on routine communication and bookings.
Elimination of no-show issues.
Ready architecture for seamless scaling to a voice assistant (Voice AI).
Technical implementation:
Integration of LLM via MCP: Connecting ChatGPT using Model Context Protocol for dynamic interaction with the backend (NocoDB, Airtable, Supabase, Google Sheets). The assistant autonomously queries current prices, services, and available time slots of masters.
Smart memory: Utilizing Supabase (PostgreSQL) to store long-term context — the bot remembers details of previous conversations with clients.
Omnichannel: Connecting the bot to the most popular communication platforms (WhatsApp, Telegram, Web Chat).
Schedule synchronization: Direct integration of scheduling systems (Google Calendar) and CRM.
Business outcome:
Saving over 80 hours a month on routine communication and bookings.
Elimination of no-show issues.
Ready architecture for seamless scaling to a voice assistant (Voice AI).