A commerce platform demonstration joining a fast storefront, an operations back office and semantic product search in one system.
- Client
- Axis
- Industry
- Retail & E-commerce
- Year
- 2026
- Services
- Web & Digital ExperienceWeb Application DevelopmentAI Search & Recommendation
Overview
What this project is.
Axis models the gap most commerce businesses live with: a storefront built for marketing and a back office built for operations, connected by exports and manual reconciliation. It demonstrates building both sides against one data model.
Challenge
The problem to solve.
When the storefront and the operational system hold separate versions of the truth, stock, pricing and fulfilment drift apart. The symptoms show up as customer complaints, but the cause is architectural.
Insight
What we noticed.
Search is where the commercial gap shows first. Shoppers describe what they want in their own words while catalogue search matches on keywords, so relevant products stay invisible and the business concludes it has a traffic problem rather than a discovery problem.
Strategy
The approach taken.
One data model, two well-designed surfaces. A prerendered storefront for speed and search visibility, an operations application for the people running the business, and semantic product search so natural-language queries return relevant results rather than nothing.
Creative Direction
How it looks and moves.
A storefront where product photography carries the page and the interface gets out of the way, paired with a deliberately utilitarian back office optimised for scanning, filtering and bulk action rather than visual impact.
Execution
What the work involved.
Shared product, inventory and order data model
Prerendered storefront with dynamic pricing and stock
Semantic product search with keyword fallback
Operations back office for catalogue, orders and fulfilment
Payment and shipping integrations
Analytics joining marketing activity to fulfilment
Deliverables
- Storefront
- Operations application
- Search service
- Integrations
- Analytics
- Deployment pipeline
Stack
- Next.js
- TypeScript
- Node.js
- PostgreSQL
- Redis
- Vector search
- Cloudflare
What it sets out to achieve
The outcome the work is built for.
This is a capability demonstration, so the outcomes below describe design intent rather than measured performance. We publish numbers only where a client has verified and approved them.
One version of the truth
Storefront and operations read the same data instead of reconciling two copies.
Findable products
Semantic search returns relevant results for the way shoppers actually describe things.
Fast where it matters
Prerendered pages for speed and search visibility, dynamic only where the data must be live.
