Applied AI · Retail intelligence
Computer vision loyalty
Using computer vision and event-driven cloud services to make loyalty recognition work without a physical card.
KueMinds
Co-Founder, Principal Engineer · architecture and implementation
Result
Cardless customer recognition connected in-store interest signals with relevant follow-up offers.
How the work connects
- Customer recognition
- Presence and shelf-interest events
- Azure services and queues
- Business notifications and offers
Context
A retail loyalty experience normally begins at checkout. I built capabilities that connected customer recognition and in-store behavior to business notifications and follow-up offers.
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.
- Built mobile and web touchpoints alongside the event-driven Azure services.
Disciplines
- Computer vision
- Event-driven architecture
- Retail AI
- Azure
Contact
Start a conversation.
If my work is relevant to something you are building, I would be glad to hear from you.