AI-Enabled Apps

Artificial intelligence is gaining ground in almost every area of daily life.

    Whether in communications, work, or entertainment, the smartphone is becoming the most significant AI interface. Often, however, apps fall short of their own capabilities. We assist app manufacturers and AI artisans in realising the full technical potential of state-of-the-art, AI-powered apps.

    inovex: where apps meet AI

    Leading app manufacturers are successfully building on new technologies, such as augmented reality or object and image recognition, in their products. The wider market, however, is slow to take advantage of the capabilities of the latest generations of smartphones. In many cases, the problem is less a lack of good ideas and more a lack of the requisite knowledge for using and integrating artificial intelligence.

    Our recognised experts have extensive experience in implementing AI-enabled apps and related technologies such as TensorFlow Lite. In order to find the optimal solution in each case, they not only use established systems, but they also carry out research to expand the possibilities for implementing AI in apps. Our assistance enables our customers to create faster, more future-proof app functions.

    Apps for AI solutions

    Manufacturers of AI systems can leverage our expertise to realise their plans for new apps. We’ll put your AI solution into practice! Our UI/UX qualifications makes us the perfect development partner. We will embed your solution into an attractive, customer-centric interface and work with you to jointly create a new app. All our offerings are part of a comprehensive range of digital services.

    Case Study

    AI-enabled Apps

    Our offerings expand AI in apps

    We are perfectly positioned to respond flexibly to the project requirements of our customers – no matter where they are in the product development process. Once the idea for a new function or app has been floated, we can use our workshop offerings to sharpen the vision and develop concrete product ideas.

    We are happy either to place our experienced teams at our customers’ disposal or to support their existing teams, both during the solution implementation process and later during DevOps operations.

    Intelligent hardware enables novel approaches

    The latest advances in smartphone hardware performance have opened the doors for new approaches in app development. Today’s smartphone hardware can perform a variety of AI tasks, including:

    • Text recognition: intelligent autocomplete and predictive text, read-aloud functions
    • Image recognition: recognition of vouchers and gift cards, image captioning, conversion to text
    • Object recognition: measuring of objects and furniture, size advice for online shopping
    • Augmented reality: previewing objects in spaces

    AI creates new shopping experiences

    We have helped customers deploy their solutions to create new online shopping experiences. One project involved the creation of an app function which uses smartphones’ object recognition capabilities to facilitate and personalise mobile shopping.

    As the project leveraged new smartphone functions which were not yet extensively used and tested, we carried out pioneering research. It was a success: by extending the scope of functions, we were able to exceed our customer’s expectations.

    Case Study

    spotsize: AI helps shoe shoppers determine the right size for a better user experience

    spotsize has developed a solution which turns online shops into the shoe-shopping experience customers are familiar with from brick-and-mortar stores. Using an augmented reality (AR) solution, the spotsize application takes over the shoe-fitter’s role. With the help of machine learning, the program uses a smartphone camera to measure customers’ feet to determine the appropriate shoe size.

    Get in touch!

    Florian Wilhelm

    Head of Data Science

    Blog

    AI-enabled Apps

    Deep Learning for Mobile Devices with TensorFlow Lite: Train Your Custom Object Detector

    This is the second article of our blog post series about TensorFlow Mobile. The first post tackled some of the theoretical backgrounds of on-device machine learning, including quantization and state-of-the-art model architectures. This article deals with quantization-aware model training with the TensorFlow Object Detection API. The third part of this series will describe how you […]