Improve shopping experience and automate retailers’ efficiency

Product Recognition Solutions

Computer vision-based product recognition solutions are primarily employed in the retail sector, with a specific emphasis on customised solutions designed to detect and categorise items displayed on store shelves. These applications are commonly used for analysing planograms and facilitating automated checkout processes.

Planogram compliance

Utilising cameras and mobile phones with computer vision-powered applications to analyse planograms and ensure adherence to the store’s strategy represents another move toward digitising the retail environment.

Automated checkout

Automated computer vision-powered systems improve the shopping experience by reducing waiting times, enhancing convenience for customers, and decreasing costs on the retailers’ side.

Store stock audit

Store stock audits empowered by computer vision streamline and enhance the process of inventory management, providing real-time insights into stock levels and discrepancies.

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Key prerequisites for implementing Product Recognition Solutions

Data quality

Just like with many other artificial intelligence and machine learning applications, the success of product recognition solutions is intricately linked to the quantity and quality of the data used during the model training phase.

Technology selection

When it comes to recognizing specific image classes, data quality, and various other factors, more technological options are at our disposal. Our responsibility lies in evaluating and choosing the right technology mix.

Data annotations

Properly annotated data, aligned with the expectations of the AI engineers responsible for training the model, can vastly improve the accuracy of the models.


Management of the expectations and proceeding step-by-step improves the overall satisfaction with the project development and implementation.

Key steps to your Computer-vision enablement journey

Usual lifecycle of computer vision-powered product recognition project

01 Challenges and goals

02 Understanding the data

03 Model experimentation

04 Benchmarks and targets

05 Evaluate, adjust, repeat

Recognizing your specific challenges and clearly outlining the goals we intend to achieve through our computer vision-powered solution is a vital and crucial first step in our collaboration.

Whether you possess in-house data or intend to employ existing datasets, following an understanding of your business objectives, the first step involves data exploration and the thorough assessment of data quality, consistency, and annotations.

Manual model training, conducted using the previously collected and refined data, yields certain outcomes. Following an evaluation of these results, we may need to iterate through this process several times before achieving the desired levels of accuracy, reliability, and solution stability.

Defining an acceptable level of accuracy, addressing edge cases, and determining the time and budget allocated for refining the model and data to attain optimal results are critical considerations. These aspects should be clearly outlined as benchmarks and metrics following their assessment in each iteration.

The evaluation of iterations, guided by established metrics, continues until the predetermined goals are met. Once these objectives are achieved, the solution is deemed ready for deployment and can be automated through an MLOps approach.

Challenges we solve

  • Inaccurate inventory management often leads to stock discrepancies, overstocking, or stockouts, which affect sales and customer trust.

  • Manual and disjointed operational processes that slow down business activities.

  • Lack of market insights to understand market trends, customer preferences, and product performance.

Take the next step

Let’s treat the core problems, not symptoms.

Estimate my project

Receive a personalised project estimate and take the first step towards bringing your idea to life.

Discover success stories

Explore our case studies and find out how we have helped some of our clients from around the world.

Benefits you can get

For startups

Product recognition solutions enable startups to optimise operations, personalise customer experiences, and scale efficiently, all while keeping costs under control.

  • Rapid market adaptation
  • Cost efficiency in operations through automated inventory and product management
  • Enhanced customer engagement with technology-driven shopping experiences
  • Data-driven decision making

  • For small and medium-sized businesses

    Small and medium-sized businesses often face the challenge of scaling operations while maintaining a personalised touch with their customer base.

  • Streamlined inventory management
  • Personalised customer experiences
  • Operational cost reduction
  • Market insight and agility

  • For enterprises

    Product Recognition Solutions offer scalability, operational excellence, and a deep understanding of customer and market dynamics. Enterprises can leverage this technology to optimise global supply chains and deliver exceptional customer experiences at scale.

  • Global supply chain optimisation
  • Personalised marketing and shopping experiences
  • Reinforced the brand's position
  • Strategic data usage

  • Case studies

    Custom Mobile App for Dog Owners

    Mobile App

    Modern technology can help owners care for their dogs and keep them safe. GPS tracks and saves dogs’ history for their whole life, easily transfers it to new owners and ensures the security and detectability of the animal.

    Read case

    Golf Training App Powered by IoT

    Software Development

    A golf training app that helps players improve their unique golf style. An opportunity for a deep configuration of the swing goal, great visual support, advanced algorithms, and effective feedback makes this project a revolution for golf!

    Read case

    Point of Sales SaaS Solution


    ZempCenter is a multifunctional Point of Sales mobile app that helps retail companies to manage orders, check inventory and stock count, generate employee reports, perform convenient transactions, and see sales reports.

    Read case

    All-in-one Solution App for Local Businesses

    Social Network

    A native iOS and Android app that connects neighbours and helps local businesses to grow within local communities. Bestyn includes posts sharing, private chats, stories and built-in editor for their creation, and tools for promoting local businesses.

    Read case

    Mobile Payment and Virtual Terminal App

    Mobile App

    The SkipCash mobile payment app is operated in Qatar, where common PoS terminals are not widespread. SkipCash tries to solve this problem with a mobile payment app that replaces the payment terminal on the seller's side and replaces the payment card on the client's side.


    Read case
    Altamira financial advisors - financial stability - mobile banking - financial management

    Slovak National Theater Web Development


    We took over the maintenance, continuous improvement, and further development of the website for the most famous and largest Slovak cultural institution – Slovak National Theater.

    Read case

    People also asked

    What is AI in computer vision?

    AI in computer vision refers to the implementation of artificial intelligence techniques to enable computers and systems to derive meaningful information from digital images, videos, and other visual inputs. It involves training machines to interpret and understand the visual world in a way that mimics human vision, using deep learning models and neural networks.

    Is computer vision always AI?

    Yes, computer vision solutions utilise AI techniques, particularly machine learning algorithms, to interpret visual data. However, not all AI involves computer vision. AI can be applied in other domains like speech recognition, analytics, and language translation. Get in touch to discover more!

    Can AI computer vision predict?

    Yes, AI computer vision can predict outcomes based on visual data analysis. By training on large datasets, these systems can identify patterns and make predictions, such as forecasting trends, detecting potential defects in manufacturing, or anticipating movements in autonomous vehicles.

    What is AI recognition?

    AI recognition refers to the ability of AI systems to identify and understand patterns, objects, speech, text, or data. Computer vision often involves recognizing and interpreting visual elements in images or videos, such as facial recognition, product recognition, object detection, and scene analysis. Contact us to learn how AI recognition can benefit your business.

    How can AI help with product development?

    AI can significantly facilitate product development by analysing market trends, customer preferences, and feedback. It can also streamline the design process through predictive modeling, automate testing and quality control with precision, and enhance customisation and personalisation of products based on consumer data analysis. For example, by integrating AI product recognition technology, retail stores can swiftly identify items for inventory management and enhance customer shopping experiences. Contact us to learn more!

    What is visual recognition AI?

    Visual recognition AI is a technology that enables computers to identify and process visual data from the world around them. This includes identifying objects, faces, scenes, and activities in images and videos. It’s widely used in various applications, from security surveillance to healthcare diagnostics and consumer applications like photo tagging. For example, the latest advancements in computer vision recognition have significantly improved the accuracy of automated facial recognition systems used in security applications.

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