Web2 Application
Last updated
Last updated
The PollenPost application architecture is an integrated structure that covers the entire process from user interaction to data storage in the database. This architecture ensures the seamless operation of components such as User Interface (UI), Business Logic, and Data Management, enabling the secure and efficient processing, management, and storage of user inputs.
Access requests to the platform are handled by the API Gateway, which also manages user authentication and authorization. Upon successful authentication, requests are directed to the Frontend components via the Load Balancer. The Frontend includes multiple modules, such as User Management, Reviews, Wishlists, and Practical Tips, which handle various user operations. User data is transmitted from the Frontend to microservices, each of which performs a specific function.
On the Backend, microservices handle database operations through the API Gateway. Data is securely stored and retrieved as needed. This architecture optimizes PollenPost’s user experience while maintaining high standards in data security and management. The processing and storage of data derived from user interactions enhance the system's scalability and performance.
PollenPost’s integrated structure enables users to interact with the platform smoothly and securely. This architecture makes it possible for PollenPost to offer a reliable, efficient, and flexible platform for both users and business partners.
AI Integration and Modular Structure
The platform’s AI modules leverage advanced machine learning techniques to evaluate user-generated content and generate summaries about users and products. PollenPost’s Validator AI uses fine-tuning methods of powerful language models from OpenAI to analyze content within platform modules. This analysis is conducted based on various criteria such as relevance, coherence, sentiment, and authenticity. The AI model of the platform has been trained on a large dataset representing high-quality content, equipping it with the ability to accurately distinguish poorly structured inputs. Each piece of content is assessed through various scoring systems that reflect quality.
The platform’s AI infrastructure includes modules like the Summarizer AI to provide effective and reliable summaries of users and products. These modules standardize user-generated data through the Preprocessing Module and identify and extract necessary text features using the Feature Extraction Module. The Evaluation Module analyzes these features according to quality criteria, while the Scoring Module synthesizes the evaluation results to assign a comprehensive score to the content piece. Our AI algorithms aim to continuously enhance user experience by providing a robust technical foundation across all aspects of the platform. This approach not only supports users in their decision-making processes but also improves the platform’s overall performance and reliability.
PollenPost’s architecture is designed as a horizontally scalable system that can handle increasing loads by adding new servers, providing high availability. The API Gateway supports scalability and high availability through load balancing and request routing functions. Security measures such as authentication, authorization, and data encryption are implemented to prevent unauthorized access and data breaches. The system delivers high performance with fast data processing and low latency. APIs and data integration tools facilitate compatibility and integration with different data sources and third-party services. The microservices architecture enables flexibility and modularity through independent development, deployment, and scaling. Reliability is maintained through data integrity and consistency protection, error detection, and recovery mechanisms. Maintenance and manageability are simplified with centralized logging and monitoring tools. User experience is optimized with user-friendly interfaces and fast response times, with continuous improvements driven by user feedback.
