Inspiration

Small businesses using WhatsApp often struggle to manage customer messages efficiently. Orders, complaints, inquiries, and feedback get mixed together, causing delays and poor customer experience. We wanted to create a lightweight automation system that helps businesses organize conversations, respond faster, and monitor activity in real time without needing expensive CRM software.

What it does

Tell5 is a WhatsApp workflow automation agent built with FastAPI. It receives customer messages through Twilio WhatsApp integration, automatically categorizes them, stores conversations and orders in a PostgreSQL database, and sends intelligent auto-replies.

The platform also provides a real-time dashboard where businesses can monitor conversations, track orders, view analytics, and manage notifications.

Main features include:

• WhatsApp message automation
• AI-assisted message categorization
• Order tracking system
• Auto-reply workflows
• Real-time admin dashboard
• Notification system
• Async backend architecture for high performance

How we built it

We built Tell5 using:

• FastAPI for the backend API
• PostgreSQL with SQLAlchemy ORM for database management
• Twilio WhatsApp API for messaging integration
• Tailwind CSS and Chart.js for the dashboard UI
• Async Python architecture using asyncio and asyncpg
• Gemini AI integration for intelligent response drafting and categorization fallback

The system processes incoming webhook requests from Twilio, categorizes messages, stores the data, and updates the dashboard in real time.

Challenges we ran into

One of the biggest challenges was handling real-time WhatsApp webhook communication while maintaining clean async database operations. We also faced difficulties designing reliable message categorization logic that works well with both keyword matching and AI-assisted classification.

Another challenge was ensuring the dashboard updated smoothly while handling multiple message events and notifications efficiently.

Accomplishments that we're proud of

We are proud that we successfully built a complete end-to-end WhatsApp business automation platform with:

• Real-time conversation tracking
• Automated customer responses
• AI-assisted workflow support
• Production-ready API structure
• Scalable async architecture
• Clean and responsive dashboard interface

We also designed the project to be easy to deploy on platforms like Railway, Render, or Heroku.

What we learned

Through this project, we learned:

• How to build scalable async systems with FastAPI
• Webhook handling and WhatsApp API integration
• Real-time workflow automation concepts
• Database modeling for messaging systems
• Combining AI-assisted categorization with traditional logic
• Better backend architecture and deployment practices

This project also helped us understand how automation tools can improve customer communication for small and medium-sized businesses.

Built With

• ai
• api
• architecture
• asyncio
• asyncpg
• chart.js
• docker
• fastapi
• gemini
• git
• github
• html/css
• orm
• postgresql
• python
• render
• rest
• sqlalchemy
• tailwind
• twilio
• uvicorn
• webhooks
• whatsapp