Availability means different things
The storefront, the warehouse, and the marketplace listing each hold a version of stock. Small drifts become oversells the moment a promotion lands.
E-commerce & Retail
Storefronts that keep the promise they make at checkout
We connect the buying journey to operational truth, so pricing, availability, and delivery dates stay honest through peak traffic and across every channel you sell on.
Sub-second
storefront response at campaign peak
One promise
availability shared across every channel
Margin-aware
experiments measured past the click
The hard part
Where the promise made at checkout comes apart
Conversion is only half the system. Promotions, inventory, tax, payment, and fulfilment all have to agree during a traffic spike, on a marketplace listing, and in a store two time zones away. When they disagree, the cost shows up as oversells, refunds, and a support queue nobody budgeted for. We build the commerce layer and the operational layer as one system with a single availability promise.
Promotion logic accumulates
Every campaign adds a rule. Without a pricing engine that can explain a final figure, nobody can safely remove anything and margin quietly leaks.
Peak is the real test
The architecture that is comfortable in March fails on the busiest hour of the year, usually at the least recoverable point in the funnel.
What we build
The commerce layer, front to warehouse
One tile leads because it is where most of the value sits; the rest are the pieces that have to agree with it before a customer ever sees a price.
Composable storefront and checkout
Fast, cache-aware storefronts with a checkout that degrades gracefully when a payment or tax provider slows down.
- Edge rendering
- Headless
- Resilient checkout
Catalog, pricing, and promotions
A pricing engine that can explain how it reached a number, with promotion stacking rules that are testable before they go live.
- Price rules
- Stacking
- Explainability
Inventory and availability
One availability service with reservations, safety stock, and channel allocation, so the promise on the page matches the shelf.
- Reservations
- Allocation
- Safety stock
Order orchestration and fulfilment
Order routing, splits, partial shipments, returns, and exchanges modelled as states rather than special cases in the checkout code.
- Routing
- Splits
- Returns
Customer data and personalisation
Unified profiles, segmentation, and recommendations grounded in behaviour you actually own rather than a third-party guess.
- CDP
- Segments
- Recommendations
Experimentation that reaches margin
Server-side experiments wired to contribution margin and return rate, not just add-to-cart, so wins survive contact with operations.
- Server-side tests
- Guardrails
- Margin
How we work
From one traced order to a rehearsed peak
We start with the order you already take and finish with the busiest hour of your year, run in advance rather than discovered live.
Step 1: Trace one order end to end
We follow a single order from impression to delivered and returned, and record every system that holds an opinion about it.
Step 2: Establish one availability truth
A single service owns what is sellable. Every channel reads from it, so the promise is consistent before we touch the front end.
Step 3: Rebuild the journey incrementally
We move the storefront and checkout in slices behind routing rules, keeping the existing platform live throughout.
Step 4: Load test against peak
Sustained load and failure injection at your actual campaign profile, so the busiest hour is rehearsed rather than survived.
What changes
What the business notices after launch
What you get
- Faster journeys without fragile checkout logic
- One availability promise across every channel
- Promotions that can be reasoned about and retired
- Experiments tied to margin, not clicks alone
Systems we integrate
- Shopify
- commercetools
- Stripe
- Adyen
- Algolia
- Klaviyo
- NetSuite
- Avalara
Standards we build against
- PCI DSS
- GDPR / CCPA
- WCAG 2.2 AA
- Core Web Vitals
Questions
What commerce teams ask us first
Usually neither in one move. We identify the constraint first, which is often availability or pricing rather than the storefront, and replace that piece behind a stable interface. A full replatform is a decision you make once the expensive part is already proven.
Make the storefront and the warehouse agree
Tell us where availability, pricing, or fulfilment stops matching what the customer was shown. We will come back with the constraint, the fix, and a slice we can ship before your next peak.