Riyaah

Riyaah needed a commerce platform that could handle a large curated catalog, regional payment and delivery rules, and an AI-assisted shopping experience - Rima - without sacrificing checkout reliability during peak campaigns.

Off-the-shelf themes could not model Saudi market logistics, authentic brand sourcing workflows, and the product-discovery UX the brand promised on the App Store and web.

Before build, SparkScribe worked with Riyaah to translate their E-commerce Platform goals into an actionable plan - not an off-the-shelf template.

Discovery & planning

• Mapped KSA delivery zones, authentic brand sourcing, and checkout rules before choosing storefront patterns.
• Connected Rima AI recommendations to live catalog, inventory, and price data - not static chatbot scripts.
• Separated merchandising, support, and admin roles so operations could run campaigns without engineering tickets.

Our engagement covered Backend development, Catalog APIs, Payment integration, Admin tooling - scoped in phases with staging parity and admin self-service so Riyaah could run day-to-day operations without waiting on engineering.

We built a Django backend with REST APIs for catalog, cart, checkout, and order management, paired with a React storefront tuned for mobile-first beauty shopping.

Payment gateways, tax, and fulfillment hooks were modeled explicitly with webhook handling and admin reconciliation tools. Rima's recommendation flows connect to live catalog and inventory data rather than static prompts.

Operations teams manage categories, promotions, and delivery zones through Django admin with role boundaries for merchandising vs. support staff.

Riyaah launched as a premium beauty destination with same-day Riyadh delivery and nationwide coverage - supporting thousands of SKUs across skincare, makeup, fragrance, and grooming.

• Market fit: Catalog and checkout logic reflect KSA delivery zones and authentic distributor sourcing.
• AI discovery: Rima provides budget- and routine-aware recommendations tied to live product data.
• Operational control: Merchandising and support teams manage catalog and orders without developer tickets for routine changes.
• Scalable foundation: Architecture supports ongoing category expansion and campaign traffic.

Technologies we used

• Python
• Django
• payments
• AWS
• React

How we applied the stack

Django provides catalog, cart, checkout, and order APIs consumed by a React storefront tuned for mobile beauty shopping. Payment gateways and fulfillment webhooks include reconciliation tooling in admin. AWS hosts the platform with environment separation for staging and production campaigns.