Unifying Scattered AI Pilots into One Governed Commerce Stack for an Omnichannel Retailer
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Problem
Six pilots, zero governance
A 45-store omnichannel general retailer had accumulated six disconnected AI pilots — search relevance, a support chatbot, demand forecasting, dynamic pricing and two abandoned proofs of concept — each holding its own copy of product and customer data. Nobody could say which models touched which records, vendor invoices overlapped, and the finance team had frozen further AI spend until someone imposed order.
Solution
One governed integration layer
We audited every pilot, retired the overlapping tools, and built a shared integration layer: a single governed data pipeline feeding all models, a central model registry with role-based access controls, and automated monitoring with audit logging on every prediction service. Surviving use cases were re-platformed onto this stack with documented data lineage and a standardised launch checklist for new ones.
Measurable Impact
What changed after launch
Six standalone AI pilots consolidated into three governed production services within 5 months
Overlapping AI vendor and infrastructure spend reduced by 31% after tool retirement
Time to stand up a new AI use case cut from roughly 12 weeks to 4
100% of production models now covered by automated data-access audit logs and monthly drift reviews
Tech & Tools Used
What powered the build
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