NovaMart — AI-Powered E-Commerce Automation Suite

Four connected AI workflows that turn every customer action — order, support ticket, abandoned cart, low stock — into an automated response.

Everything after checkout is still done by hand for most stores — and it doesn't scale. Abandoned carts go unrecovered with no follow-up, support tickets are read and routed manually, order confirmations are pushed out by a person, and stock-outs are only discovered after they've already cost sales.

I built NovaMart, a Next.js 16 storefront backed by four orchestrated n8n workflows that automate the entire post-checkout lifecycle. The moment a customer places an order, abandons a cart, or files a support request, the system takes over: orders move through confirm → ship → deliver → review automatically with every step visible in Slack; GPT-4o-mini classifies incoming support requests and routes them without a human in the loop; idle carts trigger timed recovery emails with a discount nudge; and daily inventory checks flag low stock and auto-pause zero-stock items before they turn into lost sales.

A single Supabase database acts as the one source of truth across the entire system, so there's no fragmented data between the storefront, automation layer, and support tools.

Results: Zero manual triage in the support loop, recovered revenue from carts that would otherwise have been lost, one unified source of truth instead of scattered spreadsheets, and inventory management that's proactive instead of reactive.

Stack: Next.js 16 (storefront) · Supabase (database, auth, real-time) · n8n (4 orchestrated workflows) · GPT-4o-mini (support classification) · Slack (team alerts) · Gmail API (customer communications).

If your store still runs on manual order tracking, ad-hoc support replies, or spreadsheet inventory checks, this same 4-workflow system can be adapted to your storefront in days.