AmpEnergy
AmpEnergy is a UAE-based SaaS startup that partnered with Vilmate to launch an MVP for an energy analytics platform.
The product provides smart analytics of power consumption through interactive dashboards, helping commercial and industrial consumers analyze and optimize their energy use.
The challenge
AmpEnergy planned to build an MVP that would help consumers accelerate energy performance through smart analytics of power consumption.
The product required a scalable, reliable, and cost-effective serverless architecture capable of processing large amounts of energy analytics data. Customers also needed easy-to-navigate interactive dashboards to analyze and optimize energy consumption.
Our approach
The work began with a thorough analysis of the product requirements and expected platform load.
Prioritize commercial value
The Vilmate team evaluated potential features based on the commercial value they could bring to the customer, taking into account opportunity size, development time, and costs.
Plan for performance and scalability
The technical direction was defined with a large number of daily visitors and computations in mind. Scalability, reliability, and operational costs were considered when planning the software architecture.
The solution
The resulting MVP connected energy consumers with the IoT engineers responsible for installing and maintaining the equipment that collects data from connected devices.
Serverless architecture
The Vilmate team designed the solution’s serverless architecture using AWS-managed services, optimizing performance for a large number of daily visitors and computations. The combination of these services supported efficient computation and streaming of high-frequency event data.
Backend and data processing
The backend was built with Python and AWS Lambda. It connects to IoT data from consumers’ connected devices on a regular schedule, processes it, and pushes updates to the data visualization dashboards in the web application.
Frontend and data storage
The frontend was developed with React and AWS Amplify. The data storage layer consisted of secured RDS with Aurora Serverless and DynamoDB clusters.
Platform scalability
The use of Function-as-a-Service and AWS-managed services provided scalability while reducing operational costs. The chosen architecture also supported efficient and reliable data visualization for the SaaS platform.
