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Built on Your Retail BI Warehouse

Next-Level Data Platform for Retail AI Applications

The Cybex Retail AI Data Hub turns your Retail BI data warehouse into a feature-ready platform incorporating data science, serving allocation, replenishment, forecasting, price & promo, and store ops with trustworthy, real-time data.

SLAs for freshness Data lineage & versioning Feature store ready

Unified Data Flow

Unified Data Flow Diagram A diagram showing data flowing from Retail Sources, through a Retail BI Data Warehouse, to an AI Feature Store, and finally to AI Applications. Retail Sources • POS / eCom • ERP / WMS • Planning & Merch • Vendor & Marketplace • Customer & Loyalty • Supply & Logistics • Pricing & Promo • Footfall & Sensors Retail BI Data Warehouse • Conformed dimensions (Style, SKU, Site, Calendar 4-5-4) • Facts (Sales, InventoryOH, Orders, Receipts, Transfers) • SCD, lineage, quality rules & contracts • Near real-time ingestion w/ CDC streams AI Feature Store • SiteIX, SizeIX, SeasonIX • AvgWeeklyUnits, WOS • Deficit/Surplus, Elasticities • Price/Promo features • Embeddings for products/stores AI Applications Allocation • Replenishment • Forecast • Assortment • CRM

Sources → Conformed Warehouse → Feature Store → AI Apps. Full lineage, quality gates, and SLAs throughout.

Built on What You Already Trust

Leverages your existing Retail BI warehouse and conformed models—no rip & replace. Keep your POS/ERP as systems of record.

Feature-Ready for AI

Delivers curated features (SiteIX, SizeIX, WOS, elasticities) that plug directly into allocation, replenishment, forecasting, and pricing models.

Governed, Fast, Reliable

Data contracts, quality checks, lineage, and versioning—backed by SLAs for freshness so ops teams can depend on it daily.

Reference Architecture

Compatible with Azure, AWS, GCP, and on-prem SQL Server
  1. Ingest: Batch & CDC streams from POS, eCom, ERP/WMS, planning, loyalty.
  2. Model: Conformed dimensions (Style, SKU, Site, 4-5-4 calendar), retail facts (Sales, InventoryOH, Orders, Receipts, Transfers).
  3. Curate: Marts for allocation/replenishment, price/promo, forecast, and store ops.
  4. Serve: AI Feature Store (online/offline), SQL endpoints, and governed APIs.
  5. Observe: Lineage, tests, anomaly alerts, and freshness dashboards.
Supports mixed latency: sub-hour for ops; daily for finance/merch; weekly for strategy.

Plug-and-Play Integrations

Google Cloud
Shopify
SQL Server
Magento
Microsoft Azure
Amazon AWS

Adapters map native schemas into conformed retail models so downstream AI features are consistent and reusable.

What’s Inside

AI Feature Store

  • • SiteIX, SizeIX, SeasonIX
  • • AvgWeeklyUnits, WOS, Deficit/Surplus
  • • Price/PVM features, promo lift factors
  • • Embeddings for products & stores

Operational Data Marts

  • • Allocation & Replenishment
  • • Forecasting (4, 13, 26 weeks)
  • • Price & Promo Science
  • • Store Ops & Workforce insights

Quality & Lineage

  • • Data contracts & schema checks
  • • Freshness SLAs & incident alerts
  • • End-to-end lineage & versioning

Performance

  • • Columnar storage & vector indexes
  • • Caching for hot features
  • • Online/Offline stores for training & serving

APIs & Access

  • • SQL endpoints & REST/GraphQL
  • • Python connectors (pandas/SQLAlchemy)
  • • Role-based views for BI & apps

Retail Calendar & Seasonality

  • • 4-5-4 calendar support
  • • Season curves & size curves
  • • LY vs TY normalization

Core Retail Entities

Examples from conformed models
Entity Key Fields Notes
Style / SKU Style, Color, Size, SKU, Season Maps to product hierarchy; supports embeddings & size curves.
Site SiteID, Region, Cluster, SquareFt Used in SiteIX, demand clustering, and allocation tiers.
Sales (factSales) OrderDate, SiteID, SKU, Units, Net, GM Supports AvgWeeklyUnits, LY/TY comps, PVM analysis.
InventoryOH SiteID, SKU, OnHand, QtyAlloc Feeds WOS, deficit/surplus, and transfer suggestions.
Transfers & Receipts From/To SiteID, SKU, Qty, Dates Improves lead-time aware replenishment.
Customers CustomerID, Segment, RFM Drives CRM, promo targeting, and store mix.

Security, Governance & Observability

Access Control

SSO, RBAC/ABAC, row-/column-level security, PII tokenization.

Data Contracts

Schema & quality checks on ingest; breaking changes blocked by policy.

Lineage & SLAs

Column-level lineage, freshness SLAs, anomaly alerts, incident runbooks.

Deployment Options

Cloud-Native

Azure/AWS/GCP managed warehouses and object storage, autoscaling compute, serverless APIs.

Hybrid

Keep POS/ERP on-prem; land data to cloud for AI features and serving.

On-Prem SQL Server

Leverage SQL Server 2025 (JSON/binary JSON), with Python ETL and SQLite edge caches where needed.

Fast start: drop-in adapters for Assortment Plan, Merchandising, Allocation, Forecasting,Store Ops,Shopify, Sales Audit. Typical pilot: 6–8 weeks from ingest to first AI decisions.

Explore Our Deep Dives

Go beyond the overview with our comprehensive blog series on retail AI, data science, and operational excellence.

Ready to activate AI on your Retail BI?

We’ll connect to your warehouse, map schemas, and light up feature stores for your first AI use cases—allocation, replenishment, forecast, price & promo, and more.

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