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Lengi enables users to learn through conversations that mimic natural dialogues with a native speaker. One of the key features of the application is the ability to check the correctness of sent messages, allowing users to eliminate errors and improve their language skills in real-time. In this project, we handled everything from start to finish, including all aspects such as market research, wireframing, prototyping, tests with users, launching on the App Store/Google Play, creating a landing page, and designing graphics.
Figma
ASP.NET Core
Flutter
UX/UI Design
Prototyping
Mobile App Development
E-learning
Languages
Artificial Intelligence
Balancing advanced AI and user experience
The main challenge in creating the Lengi app was combining advanced artificial intelligence technology with an intuitive and user-friendly interface. We aimed to create a tool that not only enables effective foreign language learning but also motivates users to practice regularly and monitor their progress.
Ensuring authentic language interactions and effective error correction
Ensuring authentic language interactions that replicate natural dialogues with native speakers was a challenge. This involved developing algorithms for contextually accurate responses in multiple languages. Additionally, we focused on ensuring the error correction system was precise and user-friendly across different proficiency levels.
Achieving goals with a small, efficient team
Being a small team required each member to take on multiple roles and work efficiently. We optimized our resources and time to meet high user demands and expectations.
Lengi aims to help users achieve higher proficiency levels in foreign languages by offering personalized learning experiences tailored to individual learning styles and progress.
The app seeks to boost users' confidence in speaking and understanding foreign languages through simulated conversations with AI, providing real-time feedback and correction.
Lengi aims to help users achieve higher proficiency levels in foreign languages by offering personalized learning experiences tailored to individual learning styles and progress.
All business matters were discussed -what exactly needs to be done, within what timeframe, and using which resources and tools.
We conducted a thorough analysis of competing language learning apps to identify their strengths and weaknesses. This involved evaluating their features, user interfaces and feedback
First, mock-ups were designed, and after approval, high-fidelity screens were created, prioritizing ease of use and visual appeal to support interactive AI conversations and seamless navigation.
We conducted usability tests with a group of users. Participants were asked to complete specific tasks using the app while we observed and recorded their interactions.
The implementation phase involved developing and coding the Lengi app, integrating AI algorithms, databases, and various systems.
All business matters were discussed -what exactly needs to be done, within what timeframe, and using which resources and tools.
We conducted a thorough analysis of competing language learning apps to identify their strengths and weaknesses. This involved evaluating their features, user interfaces and feedback
First, mock-ups were designed, and after approval, high-fidelity screens were created, prioritizing ease of use and visual appeal to support interactive AI conversations and seamless navigation.
We conducted usability tests with a group of users. Participants were asked to complete specific tasks using the app while we observed and recorded their interactions.
The implementation phase involved developing and coding the Lengi app, integrating AI algorithms, databases, and various systems.
Step 1
The development of the Lengi app, designed for both Android and iOS platforms using Flutter, began with translating the detailed UI/UX designs created in Figma into interactive and visually appealing interfaces. Flutter's capabilities allowed for efficient cross-platform development, ensuring consistency and high performance.
Step 2
Backend development was handled using ASP.NET Core, structured around a modular monolith architecture to ensure scalability and maintainability. RESTful APIs were developed to manage user authentication, profile settings, and interactions with the AI. Integration with external services, particularly the OpenAI API, was crucial for providing the app's AI-driven language learning features.
Step 3
The integration phase connected the frontend with the backend APIs, ensuring seamless data flow and communication. Extensive testing, including unit and integration tests, was conducted to ensure the app's functionality and reliability.
Step 4
Continuous Integration and Continuous Deployment (CI/CD) pipelines were established using GitHub Actions. This automated the processes for deployment, testing, and management of the app for both iOS and Android platforms, as well as the API and database services on Azure. This setup ensured smooth and efficient updates and maintenance.
We successfully achieved all the established MVP goals for the product in six months, including the following features:
3000
App downloads
12
+
Subscriptions sold
6
Months of work
Let's chat about your ideas and see how we can bring them to life. Drop us a message, and let's start this awesome journey together!
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