Data Annotation Services For Retail

Labellerr's smart feedback loop helps ML team to automate their computer vision data pipeline efficiently. Even at production!

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Discover the Power of Computer Vision for Retail
Why us

Retail companies have implemented computer vision

Retail companies have implemented computer vision based AI in their multiple business processes – sale process, inventory management, customer experience and planogram compliance etc. ML teams working on retail use cases have to deal with large amount of data which comes as images and videos.

OUr usecase

Production usecase examples

Self checkout

Self checkout

Fully automated checkout at point of sale powered by computer vision.

Buyer's Journey

Buyer's Journey

Track the activity of buyer while shopping.

Virtual Try-On

Virtual Try-On

Create digital twin of your self to try multiple cloths quickly

Planogram compliance

Planogram compliance

Track the SKU location, quanity and more fully automated.

Inventory management

Inventory management

Automate the mangement of inventory of a large warehouse

Personalisation

Personalisation

Personal recommendation based on past experience

Datasets available for retail use cases

Halloween Dataset

Dataset contains labeled images of Halloween costumes for kids, adults

95
Items
10
Classes
100
Labels
Halloween Dataset

Universal Image Embed

A dataset for the Google Universal Image Embedding

133000
Items
20
Classes
133000
Labels
Universal Image Embed

Production usecase examples

Planogram compliance

Planogram compliance

inventorymgmt

Inventory management

personalization

Personalisation

checkout

Self checkout

shopping mall

Buyer's Journey

Virtual Try On Retail Usecase

Virtual Try-On

FAQ

 What is Labellerr's focus in the retail industry?

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Labellerr is dedicated to using cutting-edge artificial intelligence (AI) solutions, particularly in the field of computer vision, to transform the retail sector.

Our primary goal is to advance computer vision AI projects for retailers by offering them cutting-edge tools and services that allow them to make the most of unlabeled data, pre-labeled datasets, and custom data collecting. Our objective is to equip the retail industry with state-of-the-art technology to tackle obstacles and stimulate creativity.

How does Labellerr support ML teams in the retail sector?

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Labellerr uses a multipronged strategy to offer strong support to ML teams in the retail industry. Our technology automates the entire process, from providing a variety of datasets to performing automatic data curation and annotation.

ML teams gain from the special "smart feedback loop" technology, which prioritises data annotation, visualises the quality of the data, and provides insightful information to improve model accuracy. The building of high-quality models is accelerated when unique workflows are combined with the automatic data annotation platform.

Can you provide examples of production use cases for Labellerr in retail?

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Labellerr has made a significant contribution to retail production use cases. Some notable examples are the use of cutting edge computer vision technology to automate quality control in manufacturing, customise customer experiences with sophisticated recommendation systems, and revolutionise inventory management through image recognition.

What datasets are available for retail use cases on Labellerr?

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A wide range of datasets tailored for retail use cases are available through Labellerr. These datasets cover a wide range of applications, such as shelf monitoring, customer behaviour research, and product recognition.

These specialised datasets can be used by ML teams to train models that specifically handle the intricacies and unique issues of the retail industry.

How can Labellerr help in building Vision/NLP/LLM models faster and at a reduced cost?

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With its single platform, Labellerr accelerates the creation of Vision, NLP, and LLM models by integrating iterative processes and a clever feedback loop.

While the cost-effective per-image price approach guarantees that ML teams may achieve faster model convergence and lower total project expenses, the automated data annotation engine further improves speed.

Why should retail companies choose Labellerr for their computer vision needs?

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Labellerr's customised approach to industry difficulties makes it the perfect alternative for retail organisations looking for computer vision solutions. End-to-end support is provided by our platform, guaranteeing safe and reliable data processing.

Labellerr is an enterprise-ready system that is user-friendly, cost-effective, and speeds up the development of models because to its transparency, privacy, and skilled workforce.

How can I request a demo of Labellerr's solutions for retail?

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To request a demo of Labellerr's retail solutions, simply visit our official website and locate the "Contact" or "Request a Demo" section. Fill in the required details, including your specific interests and retail-related requirements.

Our dedicated team will promptly respond to your request, coordinating a personalized demonstration to illustrate how Labellerr's solutions can effectively meet the unique needs of your retail business.

Build Vision/NLP/LLM Model Faster With 75% Less Cost

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