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Retail

Computer vision for retail

Monitor in-store activity, analyze consumption patterns and improve your operations with computer vision technology processed locally.

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What is it?

What is computer vision for retail?

An AI-based solution that analyzes customer behavior in real time to provide actionable operational data.

The system is deployed on your existing video surveillance infrastructure and processes images locally on an NVIDIA Jetson edge device, which guarantees full privacy and processing with no dependence on the cloud.

It detects and interprets relevant events in the environment: interactions with the sales floor, movement flows, consumption areas and activity peaks. All the data is structured and displayed through operational dashboards and reports.

Problems it solves

Turns the physical environment into a source of data for making operational decisions in real time.

  • 01

    No real metrics on customer behavior.

  • 02

    No visibility of how in-store areas or products perform.

  • 03

    Late restocking or no alert when consumption spikes.

  • 04

    No data to audit service quality or waiting times.

Users and applications

Built for operations supervisors, quality managers and management in hospitality and physical retail.

  • Operations supervisors

  • Quality managers

  • Management in hospitality and retail

Technology

High-performance computer vision processed at the edge

  • Real-time object detection and tracking models.
  • Pose estimation to analyze interactions.
  • NVIDIA Jetson edge devices for privacy and efficiency.
  • Dashboards with alerts, filters and report generation.
Key benefits

Measure and act in real time on what happens at your point of sale

  • Improve the customer experience through immediate action.

  • Detect consumption patterns and peaks with real data.

  • Optimize restocking and operations team planning.

  • Get added value from your video surveillance infrastructure.

Real use cases

Buffet Inteligente, developed together with Masterbar Online, lets you:

  • Analyze dish consumption by time slot.

  • Detect empty trays and alert the kitchen team.

  • View all activity in filterable dashboards.

  • Already deployed in three buffets with satisfactory results and operational validation.

Case studyHoReCa · Computer vision · IoT
MBO

Every buffet tray, measured to the gram

16cameras per unitA single NVIDIA Jetson AGX Thor processes the whole buffet.
Read the case
Hot buffet · liveBreakfast
Beans in tomato sauce676 servings / week
English sausage203 servings / week
Tray 3 · low levelRefill
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