Building Vendzoo: How I Built a Full Business OS for SMEs — Fraud Detection, 4 Couriers, RFM Engine & More

From COD fraud nightmares to automated intelligence: the story of building a business platform for Bangladesh's e-commerce market. 🎯 The Problem That Started Everything Picture this. A small shop owner is managing their online business. They've got WooCommerce for the website, Excel sheets for stock tracking, Pathao open on one phone, Steadfast on another, and Facebook Page orders coming in through DMs. They have a physical notebook for customer history, and absolutely no way to know if a new customer is a fraudster who'll refuse the delivery. Every morning starts with copy-pasting order details from three different places. Every afternoon is spent manually messaging courier agents. Every evening is reconciling which orders got delivered, which got returned, and how much money actually came in. This isn't a unique story. This is the daily reality of thousands of SME owners, retailers, and e-commerce merchants. I built Vendzoo to end this chaos. Vendzoo is an all-in-one SaaS Business OS: POS, Inventory, Courier, Fraud Detection, Customer Intelligence, Marketing, and Analytics, all in one dashboard. 🌐 vendzoo.com This is the story of how it was built, the real problems we solved, and the decisions that shaped the product. 🏗️ The System at a Glance Vendzoo is built on Laravel 13 with PHP 8.3 , backed by MySQL, with a Tailwind CSS v4 and Vite 8 frontend. Nothing exotic, just a solid, modern stack chosen for reliability and developer ergonomics. What makes it interesting isn't the stack. It's the three layers sitting on top of it. The core layer handles POS, orders, inventory, invoicing, and multi-user access with role-based permissions. The integration layer connects to everything a merchant already uses: WooCommerce, Shopify, Facebook Commerce, Pathao, Steadfast, RedX, Carrybee, Firebase, Telegram, SMS, WhatsApp, and Email. The intelligence layer is where Vendzoo earns its "Business OS" label: a fraud risk engine, customer segmentation, churn prediction, courier perfor