Amazon, headquartered in Seattle, Washington, is a global leader in technology and e-commerce. Founded by Jeff Bezos in 1994 as an online bookstore, Amazon has expanded into one of the world’s most influential technology companies, pioneering innovations in cloud computing, artificial intelligence, and digital services.

Engineering teams at Amazon and similar tech companies spend 10-15 minutes per person during standup meetings manually reviewing critical dashboard metrics and searching for system anomalies that could damage the user experience. This manual process is currently long and difficult, taking valuable development time and creating the opportunity for human error.

Our Smart Dashboard Monitoring Platform automates this through computer vision and machine learning, enabling engineers to locate data anomalies or errors early.

Our software provides a simple dashboard for analysis management. The system supports multiple inputs for analysis, including screenshot uploads for visual analysis, raw data file support for CSV, JSON and XML formats, and scheduled automatic metric ingestion using CloudWatch. Our system identifies visual anomalies in graphs, analyzes time-series patterns, detects spikes, drops, and unusual trends.

Each analysis generates findings that are saved and organized by dashboard, dataset, and service. Users view the results within an easy-to-use dashboard, enabling engineers to get insights and find issues at a glance. Our software records and visualizes historical patterns, enabling engineers to identify recurring issues.

The front end uses Next.js with TypeScript and Tailwind CSS. The back end leverages FastAPI with AWS services including Cognito, Rekognition, SageMaker, Lambda, CloudWatch, S3, EventBridge, DynamoDB and API Gateway.