The Intelligence
Layer retail Needs
Most retailers already have the data to transform how they operate. The constraint is the intelligence layer above it. We build it — starting with a focused Proof of Concept.
Where Retail Intelligence
Breaks Down
Retail generates more operational data per trading day than most industries produce in a month. The intelligence layer above it hasn’t kept pace.
01
Reactive Replenishment & Allocation
By the time a stockout or overstock position is visible in reporting, the commercial damage is already accumulating. Demand signals need to drive replenishment in near-real-time.
02
Planning Cycles That Can't Keep Pace
Weekly cadences and manual spreadsheet consolidation cannot respond to the speed at which market conditions and customer demand patterns now shift.
03
Fragmented Store Intelligence
Store teams make decisions on staffing, compliance, and inventory based on fragmented, delayed information across disconnected systems.
04
Intelligence Locked in Unstructured Data
A significant proportion of operational intelligence lives in PDFs, supplier emails, audit reports, and promotion briefs. Extracting and acting on it manually is slow and error-prone.
05
AI That Doesn't Connect to Systems of Record
Standalone AI projects rarely deliver lasting value. When AI outputs don’t connect into Oracle Retail, Blue Yonder, or ERP systems, the intelligence loop stays broken.
06
Models Without Retail Context
The most common reason retail AI fails is that the people building the models don’t understand what the numbers mean in a real retail trading environment.
Discover. Prove. Scale.
Every engagement follows the same discipline — because it’s the only approach that reliably delivers AI that works in production retail environments.
Eight Domains.
One Value Chain.
Each solution is available standalone or as part of a broader programme — always starting with a defined PoC.
01
Demand Forecasting & Inventory Intelligence
AI-driven forecasting calibrated for retail seasonality, promotions, and NPI — connected directly into Oracle AIP, RDF, and Blue Yonder SCPO.
02
AI-Powered Merchandising & Planning
Assortment intelligence, price optimisation, promotional effectiveness, and AI-assisted OTB management for faster, better-informed decisions.
03
Supply Chain AI & Optimisation
Replenishment intelligence, dynamic allocation, exception management, and end-to-end supply chain visibility — integrated into Oracle and Blue Yonder.
04
Store Operations AI
Real-time inventory accuracy, computer vision for planogram compliance, task intelligence, and staffing optimisation at store level.
05
Customer & Personalisation AI
Segmentation, next-best-action, churn prediction, and personalised promotion targeting connected into Oracle ORCE and loyalty platforms.
06
Generative AI & Copilot Solutions
AI Brief Ingestion, product content generation, planning narrative, supplier communication automation, and conversational copilots for buying and planning teams.
07
AI Strategy & Readiness Advisory
A structured assessment giving retailers an honest picture of data quality, integration gaps, organisational readiness, and prioritised AI roadmap.
08
Data Engineering & AI Platforms
The data lake, pipeline, MLOps, and real-time streaming infrastructure that makes reliable AI delivery possible at enterprise scale.
Connected Intelligence
AI that integrates into the systems that run your operation
Agent
Architecture
Four capabilities underpin every solution we build: Ingestion & Structuring, Reasoning & Decision Support, Orchestration & Workflow Integration, and Monitoring & Continuous Learning. The intelligence loop closes at the point of decision — not in a separate reporting tool.
Four Capabilities.
Every Solution.
Ingestion & Structuring
Connecting and structuring data from POS, warehouse, supplier, and planning systems — including unstructured sources like supplier emails, PDFs, and audit documents — into the clean, contextual data layer AI models need.
Reasoning & Decision Support
AI models that understand retail context — seasonal patterns, promotional dynamics, category-specific demand behaviours — and generate recommendations that teams can act on with confidence.
Orchestration & Workflow Integration
Translating AI outputs into actions within Oracle Retail, Blue Yonder, OMS, WMS, and store execution platforms — so the intelligence loop closes at the point of decision, not in a separate tool.
Monitoring & Continuous Learning
AI systems that learn from outcome data, flag degradation in model performance before it affects business decisions, and improve over time as trading patterns and operating models evolve.
Retail Practitioners Building AI
We understand retail context before we build the model
Our founders have spent their careers inside retail merchandising, supply chain, and store operations. We know what a demand forecast needs to account for in Q4, and why allocation decisions behave differently during promotions.
We build AI that connects into your enterprise systems
Retail AI that doesn't integrate into Oracle Retail, Blue Yonder, or your systems of record is a standalone tool people will stop using.
We start with a Proof of Concept. Every time.
Every engagement starts with a defined, time-boxed PoC — built to production quality, measured against commercial outcomes.
Our solutions are built to be maintained, not just deployed
AI models degrade when trading patterns change. We build monitoring and retraining systems.
Our Orientation
From data to decisions - retail done right.
The AI market is full of technology companies who have identified retail as a target vertical. We came the other way — and that shapes everything about how we work