AI / serverless

Renewable energy forecasting and AWS Lambda-based model support

AI/ML forecasting work supported by serverless AWS Lambda execution, with a focus on model quality, performance, and reliability under demand.

Overview

Challenge

The solution needed stronger forecasting quality and more resilient execution under load while staying lightweight and practical to operate.

Outcome

Improved forecasting accuracy by 15%, supported scalable serverless execution, and improved performance under higher-demand conditions.

Approach

What I did
  • Improved forecasting model quality
  • Used AWS Lambda for serverless execution
  • Validated behaviour through load testing
  • Optimised performance under demand
Focus areas
  • AI/ML forecasting
  • AWS Lambda
  • Serverless scaling
  • Performance testing

Workflow

01

Prepare

Worked with the inputs needed for accurate renewable forecasting.

02

Improve

Refined model logic to improve predictive quality and consistency.

03

Deploy

Wrapped the solution in serverless Lambda execution for flexible scaling.

04

Stress test

Used load testing to improve performance under higher demand.