Transform your retail data into revenue
AI-powered decisions that drive margin, optimise inventory, and accelerate growth — built on your existing warehouse, not around a SaaS vendor's data model.
The business case for retail AI
In today's retail environment, having great products is table stakes. What separates high performers from the rest is how effectively they optimise enterprise resources — inventory, capital, labour, and customer relationships — through better, faster decisions. The Cybex Retail AI Data Hub turns your existing warehouse into an intelligent decision engine with measurable outcomes across every dimension of retail operations.
Measurable improvement
Through precision allocation, dynamic pricing, and markdown optimisation — impact varies by baseline and adoption maturity.
Working capital efficiency
By matching supply to demand with AI-driven forecasting and replenishment — freeing cash for growth rather than sitting in stock.
Rapid deployment
Pilot to production in weeks, not years — built on existing data infrastructure rather than requiring a replatforming.
Strategic advantages
The architecture choice shapes what you can and can't do in the next five years. Here's the trade matrix.
What you gain
- Built on your existing Retail BI warehouse — no rip and replace
- Feature-ready data for 24+ AI use cases across the business
- Enterprise-grade governance, lineage, and freshness SLAs
- Real-time sync from POS, e-commerce, WMS, and ERP
- Flexible deployment — cloud, hybrid, or on-premise
- Pre-built integrations with Shopify, SQL Server, Azure, AWS, GCP
What you avoid
- Lengthy multi-year implementation cycles
- Vendor lock-in with inflexible SaaS solutions
- Data silos that prevent unified analytics
- Ongoing licensing costs that scale with revenue
- Manual processes prone to errors and delay
- Reactive decision-making on stale data
High-impact use cases
From cost savings to revenue generation — the platform addresses the operational challenges that actually move P&L.
Precision Allocation
Right products to right stores at the right time — maximising sell-through and protecting margins.
Intelligent Replenishment
Balance inventory with demand using AI-driven stock optimisation and automated reorder points.
Demand Forecasting
Predict sales with accuracy by decomposing trend, seasonality, promotions, and external factors.
Price & Markdown Optimisation
Maximise total margin by determining optimal pricing, promotion timing, and markdown depth.
CRM & Loyalty Intelligence
Transform customer data into strategic advantage with RFM segmentation and targeted campaigns.
Assortment Planning
Move from intuition to analytics for optimal product mix and buying decisions.
Store Operations
Forecast traffic, optimise labour scheduling, and automate task management.
Loss Prevention
Detect theft patterns and fraud before they impact margins using predictive analytics.
Size Curve Optimisation
Match inventory to true demand patterns by store — reducing markdowns and lost sales.
Purchasing Intelligence
Optimise buy quantities and vendor selection with predictive analytics on supplier performance.
Warehouse Automation
Streamline fulfilment with intelligent picking, put-away, and automated transfer suggestions.
Operational Efficiency
Eliminate manual processes and reduce costs through workflow automation and exception management.
Return on investment
Organisations implementing AI-driven decision systems typically experience material improvements across multiple dimensions. ROI compounds as adoption deepens — first-year wins fund the platform's further build-out.
Margin expansion
Better allocation, pricing decisions, and markdown discipline — with measurable basis-point improvements visible by quarter two.
Working capital efficiency
Inventory optimisation and faster turns free capital without sacrificing service level — cash released for growth investment.
Operational savings
Automated workflows, reduced shrink, and intelligent exception management compound over time into permanent cost structure improvements.
Why this architecture wins
Built on your foundation
Unlike SaaS solutions that force adaptation to their data model, Cybex works with your existing Retail BI warehouse. Conformed dimensions (Style, SKU, Site, Calendar), fact tables (Sales, Inventory, Orders), and business logic remain intact. We add an AI feature layer on top — curated features like SiteIX, SizeIX, weeks of supply, elasticities, and product embeddings that plug directly into allocation, forecasting, and pricing models.
Enterprise-grade, future-proof
Data contracts, quality checks, end-to-end lineage, and freshness SLAs mean operations teams can depend on the platform daily. The architecture supports mixed latency: sub-hour for store operations, daily for finance and merchandising, weekly for strategic planning. Deploy on Azure, AWS, GCP, or on-premise SQL Server — your choice, your control.