Challenge

Developing a Comprehensive Machine Learning-Enhanced Content Management Platform that Seamlessly Integrates ESG-focused Content from Multiple Sources. The challenges include ensuring the accuracy of the machine learning algorithm in classifying and organizing the content, enabling effective collaboration among users, and maintaining a user-friendly interface despite the complexity of the data. The platform also needs to support the addition of new functionalities and the integration of different content formats, such as articles, videos, and podcasts, including transcript sections. All while ensuring scalability and performance, accommodating a growing user base, and managing server loads during peak usage times.

Design & Development

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.

Project Scope

User Research

Collaborated with Marketing and Sales team to discover valuable insights and ensure a flawless user experience based on business goals and customer data.

Information Architecture

We created information architecture as a standard element of our UX process. Much more than a sitemap, this process maps out every avenue and path that users follow via the website.

Centralized REST API

We used a Ruby on Rails backend and REST APIs.

Search

We developed a dynamic search by author, tag and content using customized filtering techniques.

User and Content Management

This functionality managed guest users, knowledge playlist, and contents within an admin dashboard.

Machine Learning

We developed this functionality to discover and tag authors of content based on ESG topics.

User Research

Collaborated with Marketing and Sales team to discover valuable insights and ensure a flawless user experience based on business goals and customer data.

Information Architecture

We created information architecture as a standard element of our UX process. Much more than a sitemap, this process maps out every avenue and path that users follow via the website.

Centralized REST API

We used a Ruby on Rails backend and REST APIs.

Search

We developed a dynamic search by author, tag and content using customized filtering techniques.

User and Content Management

This functionality managed guest users, knowledge playlist, and contents within an admin dashboard.

Machine Learning

We developed this functionality to discover and tag authors of content based on ESG topics.

https://www.alamedadev.com/projects/gathersight