AI Ecommerce Messaging Automation

Inspiration

Ecommerce brands lose revenue due to abandoned carts, slow support, missed updates, and impersonal communication. We wanted to build a smart messaging engine that delivers personalized, real-time messages across channels while respecting privacy.

What it does

Our system detects high-value ecommerce events, generates contextual messages, delivers them WhatsApp-first with SMS fallback, and tracks performance in real-time. It ensures user consent, privacy, and measurable engagement.

How we built it

Frontend: Product catalog, cart, checkout simulation, consent modal, WhatsApp/SMS message preview, admin panel, live dashboard Backend: Event ingestion, consent & profile management, template composer, dispatcher, fallback routing, webhook simulator, conversion tracking Queue & Channels: Reliable event queue, WhatsApp/SMS adapters, Instagram preview Tech Stack: JavaScript, Python, Node.js, MongoDB, React, CSS, HTML

Challenges we ran into

Designing WhatsApp-first with SMS fallback Handling real-time metrics and dashboards Implementing strict privacy and consent rules

Accomplishments that we're proud of

Automated real-time, cross-channel messaging Built consent-first and privacy-safe architecture Enabled brands to recover abandoned carts and improve conversions Developed a scalable, professional system with reliable UI feedback

What we learned

Importance of event-to-message pipelines for real-time automation Handling masked user data and consent revocation safely Integrating AI/automation logic in production-ready systems

What's next for AI Ecommerce Messaging Automation

Multi-language support and voice-based interactions Advanced analytics dashboard with predictive insights Integration with more messaging channels and personalization AI

Built With

• api
• css
• express.js
• gateway
• html
• javascript
• mongodb
• node.js
• python
• queues
• react
• scheduler
• sms
• webhooks