What is the project
The Autonomous Store is an autonomous or hybrid retail format for grocery retailers, built on sensor fusion (computer vision and weight sensors) and artificial intelligence (AI). It enables customers to shop without queues by automatically building a virtual basket, with checkout either at an exit terminal or later via an app.
Project at a glance
Focus: Autonomous/hybrid store format using sensor fusion (computer vision + weight sensors) and AI to remove checkout queues
Key demonstrators: Continente Bom Dia autonomous pilot store (Leiria); real-time basket; large-scale camera and store calibration; large-scale people tracking; White Label App; StoreCraft digital twins; smart shelves and pallet scales; factory configuration tools; in-store hardware diagnostics; mobile installation tool; ERP (Enterprise Resource Planning) integration; annotation and neural network training pipeline automation
Operation: Customers enter, pick items, and either pay at an exit terminal or leave without interacting with a terminal and are charged later in an app; integration with FAST platform and retailer ERP
Primary pilot locations: Continente Bom Dia (Leiria); Continente Labs
Objectives
- Deliver a seamless autonomous shopping experience that removes checkout queues.
- Create and maintain an accurate real-time virtual basket using sensor fusion and AI.
- Scale calibration and tracking to large stores with high camera counts and high customer volumes.
- Improve store operations through tooling for planning, deployment, diagnostics, and product onboarding.
- Validate designs suitable for pilot-scale production with low variability and stable signal quality.
- Support retailer deployment through integrations (FAST platform and retailer ERP).
What we delivered
Development and inauguration of the Continente Bom Dia autonomous pilot store in Leiria (1,217 m²) using computer vision, smart shelves and AI, enabling autonomous shopping without requiring app installation; extensive interaction testing and improvements to virtual basket accuracy through optimized product and scale layout, weight-signal oscillation filtering, and real-time planogram-change alerts based on computer vision; integration work including FAST app/platform and retailer ERP (Enterprise Resource Planning); refactoring of large-scale camera calibration for stores with more than 1,000 cameras and more than 1,000 m², and refactoring of people tracking for large-scale deployments with peak loads and a reported ~4× reduction in tracking processing time; development of a customizable White Label App with multiple payment systems and user identification options; creation of StoreCraft for digital twin generation and simulation on Unreal Engine, including automatic camera placement from store layout; production and deployment of smart shelves, reinforced picots and adapted pallet scales tailored to the Bom Dia format; development of factory tools to parallelize camera configuration and a desktop tool for scale production enabling externalized manufacturing with reported near 0% faulty scales in a recent deployment; creation of in-store hardware diagnostics, a mobile installation tool for validating camera and shelf positioning with anonymized streams, and camera/gondola calibration process optimizations including multi-cube sample acquisition and area-based parallel calibration; implementation of a filter to eliminate false person detections from posters; and automation of data capture, anonymized annotation (CVAT), quality assurance, training and deployment pipelines for computer-vision models using Airflow.
Metrics / KPIs
Pilot store size (Continente Bom Dia, Leiria) 1,217 m²
Cameras (scale calibration reference) +1,000
Product references supported +12000
Smart shelves produced +2,500
New “products” 4
Summary
The Autonomous Store project delivers an autonomous/hybrid retail format built on computer vision, weight sensing and artificial intelligence to remove checkout queues. The flagship deployment is the Continente Bom Dia pilot store in Leiria, supported by real-time basket technology, large-scale calibration and people tracking, and integrations with FAST and retailer ERP systems. Tooling for digital twins (StoreCraft), deployment, diagnostics, and automated model training helps scale operations across complex store environments.
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