RETAIL AND E-COMMERCE
Digital engineering for retail and e-commerce
We connect product, inventory and customer data across stores, e-commerce and marketplaces. Our teams build search, forecasting and commerce platforms that help staff and customers act on consistent information.
- AI search proven across 200,000+ products
- Payment flows designed to PCI-DSS controls
- Personalization on a consent-first foundation
Connected data across retail channels.
Retail teams need to coordinate availability, product discovery and fulfilment as demand changes.
Inventory alignment
Different stock records across channels create avoidable substitutions, delays and markdowns.
Product discovery
Customers and staff need to find the right item using the language and attributes they know.
Seasonal demand
Campaigns and trading peaks require coordinated forecasts, replenishment and platform capacity.
Retail data and commerce capabilities.
Explore the services behind product discovery, inventory decisions and reliable commerce platforms.
Demand forecasting
Forecast demand at SKU and store level. Evaluate forecasting error against your existing planning baseline.
EXPLORE02Data and analytics
Turn browsing and purchase data into signal. A unified data platform across channels, with governance and lineage.
EXPLORE03AI search and personalization
Search that speaks the customer's jargon and recommendations that tailor products, pricing, and content to intent.
EXPLORE04Conversational AI
Assistants for ordering, order status, and support across web, app, and store, escalating to a human when needed.
EXPLORE05Cloud and platform engineering
Elastic, observable platforms sized for seasonal spikes, from e-commerce storefronts to national marketplaces.
EXPLORERetail systems already running at national scale.
BLACKWOODS · INDUSTRIAL DISTRIBUTION<2s
Softobiz built BlackOps for Blackwoods, an Australian industrial supplier: AI-powered search with real-time inventory synchronization on Azure. Stock update lag fell from 6+ hours to under 1 hour, and teams saved 30% of inquiry time.
Decisions across the retail journey.
A customer cannot find the right product
Product attributes and availability inform search results. Merchandising teams review relevance feedback and manage product rules.
Demand is rising in one channel
Sales and stock feeds inform store-level forecasts. Planners review exceptions and choose replenishment or allocation changes.
An order crosses systems
Order, stock and fulfilment events are reconciled across the commerce platform and ERP. Exceptions are routed to the team responsible for resolving them.
Customer data controls across retail channels.
Payment flows are designed to PCI-DSS controls, keeping cardholder data isolated and tokenized with controls to exclude it from analytics and model training.
Personalization is built on a consent-first foundation: customer data is used within the permissions the shopper granted, honoring privacy expectations and applicable consumer data regulations, with the ability to explain and unwind targeting when asked. Data lineage and access controls run through every pipeline.
- PCI-DSS payment flows with tokenized cardholder data
- Consent-first personalization within granted permissions
- Targeting you can explain and unwind on request
- Lineage and access controls through every pipeline
Continuity across trading seasons.
Through our Global Capability Center and dedicated-team model, you get a persistent pod that learns your assortment, calendar, and channels, and improves the models season over season.
You can also start narrow with a packaged conversational AI assistant and expand from there.
Questions about retail engineering.
Yes. We assess the product catalogue, search interfaces and inventory feeds to define a bounded search improvement around your existing platform.
We use your trading patterns to plan load testing, capacity and operational monitoring. Performance targets and fallback arrangements are agreed for the workload.
We define permitted data use, access and retention with your team. Consent and preference changes need to flow through the systems that use them.
Connect your retail data and customer experience.
We can review a specific customer journey or operational priority and identify the data and engineering work it needs.