Overview
We design and deploy AI vision systems that turn cameras into operational intelligence, detecting product gaps, measuring shopper behavior, and surfacing exceptions before they cost revenue.
Our vision stack is built for noisy real world environments: variable lighting, partial occlusions, and multi camera retail floors. Models are trained on your assortment and layout, then deployed with monitoring so accuracy stays production grade as products and planograms change.
Who it's for
- Retail operators chasing OOS and planogram compliance
- Ops leaders who need live floor visibility
- Digital teams integrating vision into loyalty and Echo
Capabilities
- Shelf gap & planogram detection
- People counting & zone analytics
- Queue and dwell measurement
- Edge inference with cloud sync
- Exception alerts to store ops
- API hooks into POS and inventory
Outcomes
- Real time shelf and inventory visibility
- Shopper journey and dwell analytics
- Lower out of stock and shrink impact
- Faster store level exception handling
Deliverables
- Vision model training & deployment
- Edge / cloud inference pipelines
- Operations dashboards & alerts
- Integration with store systems
- Runbooks and ops enablement
Use cases
Shelf intelligence
Detect voids, facings, and incorrect placement so replenishment happens before shoppers leave empty handed.
Shopper analytics
Understand pathing, dwell, and conversion zones to inform layout, staffing, and promotions.
Ops exception routing
Push prioritized alerts to store managers with image evidence and recommended action.
How we deliver
01
Discover
Map camera coverage, use cases, and success metrics with stakeholders.
02
Prototype
Train models on your environment and validate accuracy in live conditions.
03
Scale
Roll out inference, monitoring, and ops workflows across locations.
Common questions
Do we need new cameras?
Often existing CCTV works. We assess coverage, resolution, and angles before recommending hardware changes.
How is privacy handled?
We design for policy compliance, anonymization, retention limits, and role based access to visual evidence.
How long to first value?
A focused pilot can surface shelf and traffic signals in weeks; multi site rollout follows after accuracy thresholds are met.
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Ready to apply AI Vision?
Tell us about your environment and goals. We'll map a practical path from pilot to scale.