Applied AI · Retail intelligence
Computer vision loyalty
Using computer vision and event-driven cloud services to make loyalty recognition work without a physical card.
Outcome
Cardless customer recognition connected in-store interest signals with relevant follow-up offers.
Context
A retail loyalty experience normally begins at checkout. This concept explored how customer recognition and in-store behavior could help the business respond earlier and more personally.
Challenge
Translate computer-vision signals into useful business events and customer workflows, rather than stopping at face detection as a technical demo.
Approach
Make the system work.
- 01
Develop face-recognition capabilities for cardless loyalty identification.
- 02
Model customer presence and shelf interest as events that downstream services could act on.
- 03
Connect Azure Functions, API Management, Cosmos DB, Azure SQL, queues, and blob storage.
- 04
Design mobile and web touchpoints around the event-driven service architecture.
Impact
What changed.
- Extended loyalty recognition beyond the physical card and checkout moment.
- Connected in-store behavior with timely, relevant follow-up opportunities.
- Demonstrated how applied AI, cloud architecture, and business workflow create value together.
Disciplines
- Computer vision
- Event-driven architecture
- Retail AI
- Azure