This app combines machine learning and video streaming technologies to offer a secure, personalized online language learning experience through a subscription model.

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Our team’s partnership with the client emerged through a referral. Developing an innovative online platform dedicated to language learning was the project’s focus. Offering unlimited access to learn any language by subscription, tailored to individual employee needs, is the essence of this platform. This encapsulates the mission of the project: to provide a personalized and flexible learning environment for language acquisition, accessible through a subscription model.


At its core, the app is a dynamic and user-friendly platform for online language lessons, primarily delivered through video calls. This approach emphasizes real-time interaction and personalized learning, catering to diverse linguistic needs.

The Challenge

The most significant challenge encountered in this project revolved around the integration of a sophisticated Machine Learning (ML) model. This model plays a crucial role in ensuring the integrity and authenticity of the language learning experience. Its primary function is to verify, through advanced voice recognition technology, that the participant in each language lesson is indeed the individual who is supposed to attend. This mechanism acts as a safeguard against fraudulent use of the service. 


The process entails a unique system. When a student first joins a lesson, they are required to record a voice sample by reading a specific sentence. This initial recording serves as a baseline for future verification. During subsequent lessons, the ML model compares the student’s voice in the video against this pre-recorded sample. By analyzing various voice characteristics, the model assesses and provides a probability score indicating whether the voice in the current session matches the original sample. A low probability score triggers a flag, suggesting that the account might be accessed by an unauthorized user.


Implementing this feature was not just a technological hurdle, but also a critical aspect of maintaining the platform’s credibility and security. The challenge lies in the seamless integration of this ML model with the existing video call system, ensuring accuracy in voice comparison without compromising the user experience or lesson flow. This complex feature highlights the project’s commitment to innovative solutions and high standards of service integrity.

szymon, project manager at applover
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"Our team's journey in developing this language-learning platform was a blend of innovation and dedication. Leveraging Vue.js and Ruby on Rails, we've delivered a secure, user-focused experience, enhanced by cutting-edge machine learning. This project showcases our commitment to redefining online education."

Testimonials quote icon

Project Manager at Applover


Development time

Technological solution

The project hinged on the implementation of cutting-edge technological solutions to create a robust and innovative platform for online language learning. Two key components stood out in the project’s technological architecture:


  1. Machine Learning Model for Voice Recognition: As detailed earlier, a central feature of the platform is the integration of a Machine Learning (ML) model specializing in voice recognition. This model is instrumental in ensuring the authenticity of each user participating in the language lessons. By comparing voice samples recorded during the initial session with those in subsequent video calls, the model provides a probability score indicating whether the same individual is consistently attending the lessons. This advanced use of ML not only enhances security against fraudulent access but also showcases the project’s commitment to leveraging modern technology for improved service quality.


  1. Video streaming via Vonage Platform: The second pivotal technological aspect is the use of video streaming to facilitate language lessons through video calls. For this purpose, the project utilized the services of the Vonage platform, known for its robust API designed for video streaming applications. The choice of Vonage as a service provider underscores the project’s emphasis on delivering high-quality, reliable video communication. This platform enabled seamless, interactive video calls, which are crucial for effective language learning and engagement between instructors and students.


These two technological components — the ML model for voice verification and the Vonage platform for video streaming — collectively formed the backbone of the project. They not only addressed the specific needs of the language learning platform but also reflected a forward-thinking approach, integrating non-standard and innovative solutions to enhance user experience and operational efficiency.

ruby on rails

The Outcome

The culmination of this project was the successful creation and deployment of a fully functional online language learning platform. This platform represents a comprehensive and user-centric approach to language education, meeting and exceeding the initial project objectives.


For students, the platform offers a high degree of flexibility and personalization. They can conveniently select the language they wish to learn, choose their preferred lecturer, and schedule lessons at times when it suit them. The integrated video call feature, powered by the Vonage platform, facilitates immersive and interactive language learning sessions, enhancing the overall educational experience.


Lecturers, on the other hand, benefit from a streamlined and efficient system. They have the capability to set their schedules, join lessons seamlessly, and earn from their teaching services. This dual-sided functionality ensures that the platform caters effectively to both learners and educators, fostering an environment conducive to language acquisition and teaching.


All the initial assumptions and goals of the project have been achieved, resulting in a robust, scalable, and user-friendly platform. The success of this venture is further highlighted by the ongoing discussions with the client regarding future enhancements and expansions of the application. This ongoing engagement is a testament to the client’s satisfaction and the platform’s continued growth and innovation potential.

Meet our team!

łukasz, front-end developer at applover


Front-end Developer

Nazar, front-end developer at applover


Front-end Developer

michal nowak backend developer


Back-end Developer

bartosz back end dev


Back-end Developer

kuba qa specialist


QA Specialist

julia ux/ui designer at applover


UX / UI Designer

szymon, project manager at applover


Project Manager

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