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Retail & Commerce

E-Commerce and Omnichannel Platforms Engineered to Handle What Peak Traffic Actually Looks Like

  • Google Cloud Partner
  • 4.9/5 Clutch Rating
  • 150+ Enterprise Clients
  • Shopify & Headless Ready

Custom storefronts, inventory management, AI personalization, and unified commerce — built on an architecture that holds up during Black Friday, not just on launch day.

What We Offer

Technology Services for Retail & Commerce

Why SolveJet

Retail platforms break under pressure. We build for that pressure from day one.

A checkout flow that works at 500 concurrent users fails at 50,000. A personalisation engine that runs on a 5-second page load kills conversions. We design for the operational ceiling, not the demo.

We load-test at 10x normal traffic before every launch. Auto-scaling infrastructure, CDN caching, database read replicas, and queue-based order processing mean your platform doesn't degrade when sales campaigns hit.

We build headless storefronts that decouple your frontend from your commerce engine — so you're not rearchitecting when you outgrow Shopify or need to add a new channel.

As a Google Cloud Partner, we deploy Vertex AI recommendation models and BigQuery analytics pipelines that personalise at the product and customer level without third-party SaaS fees eating into margins.

In retail, a production bug on a campaign day costs real revenue. Our clients get direct access to the engineers who built the system — not a support ticket queue with a 4-hour SLA.

Proven Outcomes

What Good Commerce Technology Delivers

These are the benchmarks well-built retail platforms consistently move — and what we design toward on every engagement.

0%Conversion Rate Uplift from Personalisation
0%Target Customer Satisfaction Score
<2sPage Load on Peak Traffic Days
0%Our Client Retention Rate

Trusted by

Our Clients

What We Build

Reference architectures for retail and commerce technology

These illustrate the platforms we design and engineer — the technical approach, the components, and the operational outcomes they're built to deliver.

E-Commerce
<2s
Target Page Load
Auto on GCP
Peak Scaling

Headless E-Commerce Storefront

A Next.js headless storefront decoupled from the commerce engine — sub-2s page loads, advanced product catalog with variants and bundles, Stripe checkout, and Algolia-powered search. Auto-scales on GCP for peak campaigns.

Omnichannel
Real-time
Inventory Sync
Web, mobile, POS
Channels Unified

Omnichannel Inventory & Commerce Platform

A unified commerce layer connecting online, mobile, and in-store channels with a single inventory truth — real-time stock sync, click-and-collect, ship-from-store, and consistent pricing across all touchpoints.

Mobile Commerce
iOS & Android
Cross-Platform
Vertex AI
Recommendations

Mobile Commerce App (React Native / Flutter)

A cross-platform shopping app with loyalty program integration, push notifications, personalised recommendations via Vertex AI, and a native checkout flow — built offline-capable for markets with patchy connectivity.

Retail Analytics
BigQuery
Data Warehouse
Cross-channel
Attribution

Unified Retail Analytics Platform

A BigQuery-backed analytics platform consolidating POS, e-commerce, and marketing attribution data — sales by SKU, channel, and customer segment, basket analysis, and marketing ROI in a single Looker dashboard.

Our Process

How we deliver retail technology projects

A structured engagement model built for the speed and scale requirements of modern retail businesses.

01
Week 1–2

We audit your current tech stack, map customer journeys, and define integration requirements with your product, marketing, and operations teams.

02
Week 2–3

Our architects design the commerce blueprint — catalog structure, checkout flows, integration points, and scalability plan for peak traffic.

03
Week 4–16

Two-week sprints delivering working software. Core storefront and checkout first, then personalization, analytics, and integrations.

04
Week 14–18

Load testing at 10x normal traffic, checkout flow testing, payment gateway validation, and cross-device compatibility testing.

05
Week 18–20

Phased launch with A/B testing framework in place. Full team training, runbooks, and 90-day hypercare support included.

Use Cases

How retailers use our technology

From e-commerce platforms to AI personalization, see the specific problems we solve for retail businesses.

Scalable e-commerce platform built for growth

Build a high-performance storefront that handles millions of SKUs, complex product configurations, and peak traffic without performance degradation.

  • Headless storefront with sub-2-second page loads
  • Advanced product catalog with variants and bundles
  • One-page checkout with 15+ payment methods
  • Multi-currency and multi-language support
  • SEO-optimized product pages with structured data

Technology Stack

Tools and platforms we work with

We build on proven, enterprise-grade technology — and integrate with the systems you already run.

Commerce Platforms01 · 4 tools
Shopify
Salesforce
Stripe
Algolia
Cloud & Infrastructure02 · 4 tools
Google Cloud
AWS
Kubernetes
Terraform
AI & Personalization03 · 4 tools
Vertex AI
TensorFlow
BigQuery
Looker
Frontend & Mobile04 · 4 tools
React
Next.js
React Native
Flutter

FAQ

Common Questions About Retail Technology

Everything you need to know about modernizing your retail and commerce operations with SolveJet.

We build custom e-commerce platforms from scratch and work with Shopify, Shopify Plus, Salesforce Commerce Cloud, Magento/Adobe Commerce, and WooCommerce. We also build headless commerce solutions using modern frontends with any backend commerce engine.

We architect for peak traffic using auto-scaling cloud infrastructure, CDN caching, database read replicas, and queue-based order processing. We conduct load testing simulating 10x normal traffic before every major sales event.

Yes. We build unified commerce platforms that synchronize inventory, pricing, and customer data across online, mobile, and physical store channels. This includes POS integrations, click-and-collect, ship-from-store, and unified customer profiles.

AI improves retail through personalized product recommendations (increasing AOV by 15–30%), dynamic pricing optimization, demand forecasting for inventory planning, visual search, and AI-powered customer service chatbots that handle 60%+ of support queries.

A focused storefront with standard features typically takes 3–5 months. A full omnichannel platform with custom integrations, loyalty programs, and analytics ranges from 6–12 months. We use phased delivery so you can launch core features first.

Get In Touch

Tell us what
you're building.

"They don't force us to go their way; instead, they follow our way of thinking."

★★★★★Marek StrzelczykHead of New Products & IT, GS1 Polska