Horizont Labs

Project Ecosystem - High-Performance Data Processing

Client

Ecosystem (A Generative AI company)

Date

2024 / Current

Challenge

The client needed a system to handle large amounts of image and text data efficiently while ensuring compliance with regulations. The existing system was slow, inaccurate, prone to human error, and lacked automation.

Process

We researched and developed machine learning capabilities for rapid, accurate, and automated data processing. Our team developed and maintained high-performance Rust applications to handle large-scale image and text data processing. We implemented advanced machine learning techniques and GPU acceleration to optimise image processing workflows, significantly enhancing processing speed and accuracy.

Additionally, we deployed, configured, and managed production systems on AWS, leveraging AWS EMR for big data processing. We also integrated image processing modules into web applications using React.js and TypeScript, ensuring seamless user experiences. To streamline the development process, we set up a continuous integration and deployment (CI/CD) pipeline using Jenkins and GitHub Actions.

Solution

Using Rust, we built new applications with Machine Learning to enable large-scale processing and seamlessly integrated these with existing workflows and processes to minimise operational disruption. The new system improved processing efficiency and accuracy, safeguarding data integrity and accessibility. The use of advanced machine learning techniques and GPU acceleration optimised workflows, while the integration with AWS ensured effective handling of large datasets. The CI/CD pipeline facilitated rapid and reliable code deployment, enhancing overall system performance and user experience.

Results

The new system greatly improved efficiency and accuracy, ensuring data integrity and compliance. Workflows were optimised, and the system is now easier to maintain and update.