Retail Data Layer Repair
One version of the truth for inventory, product, and customer records across every channel. The unglamorous foundation every retail AI use case depends on.
Retail Operations & AI Transformation
Retail runs on operations. Make yours AI-ready.
We help retail and consumer executives turn AI ambition into operating reality: inventory and product data leadership can trust, unified commerce processes, and the governance that lets AI ship safely. Proven inside a $7B multi-brand specialty retailer and a $16B global supply chain leader.
Overview
Most retail AI initiatives do not fail at the model. They fail in the data layer beneath it: inventory records that disagree with the shelf, product hierarchies that differ by channel, and customer data split across systems that were never designed to talk.
Our Retail Operations & AI Transformation practice repairs that foundation first, then installs the operating model that keeps it clean: named data owners, a governance cadence the board actually sees, and processes that work the same way in-store, online, and in the warehouse.
The sequence matters more than the tools. Fix the data layer, install the decision rights, then scale the AI. Retailers who invert that order buy pilots. Retailers who follow it buy margin.
What We Deliver
The work, in precise form.
Unified Commerce Operating Model
Store, digital, and supply chain operations designed as one system with shared definitions, shared owners, and processes that survive peak season.
AI Governance for Retail
Decision rights, risk tiers, and review cadence for AI in pricing, forecasting, and customer experience, so use cases move from idea to governed production in weeks.
Store & Supply Chain Automation
Process automation across replenishment, reconciliation, and reporting: the repetitive work that consumes your teams and hides your margin.
The Methodology
Diagnose. Design. Deploy.
01
Diagnose
Trace where inventory, product, and customer truth breaks down across channels, and quantify what the disagreement costs in margin, markdowns, and hours.
02
Design
Architect the retail data layer, ownership model, and governance cadence that AI-driven forecasting, pricing, and store operations require.
03
Deploy
Implement in sequenced 90-day installs with disciplined change management, proving value per phase instead of promising it per deck.
The Outcome
A retail operation where AI pays for itself.
The end state: inventory accuracy leadership can act on, one product truth across channels, AI use cases shipping under real governance, and an operating model that compounds instead of firefights. Built on experience delivering $175M+ in retail and supply chain platforms.
Private Consultation
Ready to architect the next phase?
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