ECHO, a full cloud ML and AI business platform
At a Glance
ECHO, a B2B platform, chose to migrate and optimize its infrastructure on the cloud, integrating Machine Learning (ML) and Artificial Intelligence (AI) technologies to improve the efficiency and accuracy of business processes. This case study illustrates how we streamlined the architecture, implementing advanced solutions to achieve exceptional results.
Key Process
Amazon S3 and Lambda
We transferred large volumes of data to Amazon S3 for scalable and cost-effective storage. AWS Lambda functions were used to process data asynchronously, reducing processing times and improving system responsiveness.
Machine Learning for Demand Forecasting
We used Amazon SageMaker to develop and train Machine Learning models capable of accurately predicting product demand. These models allowed for inventory optimization and cost reduction.
Process Automation with AI
To automate product recognition and categorization, we implemented Amazon Rekognition.
Traffic Management with Amazon SNS
To reliably and scalably manage traffic between the various system components, we used Amazon SNS, improving the platform's resilience and efficiency.
Outcomes
Thanks to these strategic implementations, the procurement platform achieved significant improvements in terms of efficiency and innovation. The integration of cloud, ML, and AI solutions optimized procurement processes, reduced operational costs, and enhanced the quality of services offered to end-users.
60 ms
specific API response time
4x
sustainable traffic load
+10K
simultaneous streaming user capacity