ML-Powered Platform for Curating ESG Articles and Topics

ESG Data Classification and Search

Our journey began with an emphasis on design. The aim was to create a user-focused design system that ensured easy navigation and seamless interaction. We spent time understanding user flows and sketching out comprehensive wireframes to visualize the path a user would take and the layout of the platform.

We aimed for a design system that was flexible and scalable, able to accommodate a wide array of ESG-focused content types like articles, videos, and podcasts, all while maintaining a cohesive user experience. Each design element was created with reuse in mind, establishing a design language that could be consistently applied throughout the platform.

Moving from design to development, we leveraged the power of ReactJS and Ruby on Rails due to their efficiency, scalability, and maintainability. The architecture was based on reusable components, making the code more efficient and easier to maintain.

The platform allows users to register, create profiles of interest related to ESG topics using machine learning, and share curated lists. It also features an algorithm that adapts to user interactions and automatically classifies new content.

To enhance user engagement, the platform enables users to produce new content and follow experts in their fields. We're also in the process of adding new features, such as the ability to hire experts, make video calls, and handle payments, all designed to enrich the user experience.