Cloud EdTech solution with AI module
Development of custom software to provide highly automated educational services with the integration of AI assistant and analytical module to reduce the time needed for educational processes management by 20%.
The customer's EdTech company with the yearly turnover of 116 million U.S. dollars required the development of custom software with cloud deployment of new modules and partial migration to the cloud for old ones. As one of the trending and driving features for educational industry, the customer decided to add an AI-driven assistant to help the students with their courses as well as provide predictive analytics, curating assessments and suggest content useful for a student for basic processes automatisation.
Building cloud-based architecture required complete refactoring of old monolithic applications of the customer into microservices. That allowed making separate modules with educational, payment, and analytical functions and connecting them to external resources through APIs. The team paid special attention to providing a secure, flexible organization of modules and resource structure to suit the requirements of privacy legislation and company possibilities.
Besides the basic technical aspect of the migration and complete redesigning of the application, the team had to recreate the UX of the solution to make it more suitable for new students. One of the approaches included the creation of a platform with rich metadata from videos and images to turn them into useful learning resources that can be streamed cost-effectively to students anywhere.
as target market
Pecularities of implementation
Microservices architecture of the cloud solution
The core of the migration of the application was in the refactoring of the existing code into the modular structure. That allowed us to cover several goals: provide an efficient infrastructure for remote learning on a global scale, support mobile learning and omnichannel learning experiences, offer personalized learning strategies, and open the door to analysis of the student behaviour and prediction of the learner’s success. In the process of developing the team used reliable approaches to data governance and migration, network setup, automated templates and cloud resources governance to build the robust infrastructure under the conditions of live-to-live migration with a big database of users.
Unification of the data for traceability
Making data available worldwide is one of the benefits of the cloud solution together with process automation and the use of external resources through APIs. Such API-based collection of external data allows the creation of various content without its storage on the company’s servers and losing funds on infrastructure. That makes learning more fluid and information more discoverable both in terms of accessibility and data availability. Together with the AI assistant, the unification can become a powerful instrument for students and teachers allowing them to save up to 20% of the time on lesson preparation. Powerful content delivery, database, analysis, and digital end-user engagement services add to the general market compatibility of the company and broaden possibilities.
Introduction of the AI module for experience enhancement
To deliver highly personalized content recommendations for teaching and learning at scale, the team connected the specialised AI module which got learned with the data provided by the customer. It received a special privacy-enhancing firewall to exclude any random privacy violations due to the use of the live database. The model is tested on the ability to provide insights with real-time and predictive analytics, visualize, and securely share results in dashboards. That can be used by students or teachers to predict up to some extent the outcome of their learning course or provide a deeper analysis of the exam results and the reasons.
Being sure that cloud-enabled technologies become a comitative advantage in the fragmented EdTech market, the customer required fast migration regardless of any risks. The selected approach allowed the company to enrich their services without losing momentum in the market. It saved infrastructure investments as well, as far it was the starting point of the customer in the development of such a system. Even with the fact that the system migrate while being life, graduate product release allowed making the process seamless for users.
fewer expences due to cloud deployment
time saved due to automatisation
sources of data collection