Serverless AI Pipeline for Quality Inspection on AWS

Designed and deployed a serverless AI pipeline on AWS to automate visual inspection of manufacturing parts. Trained a convolutional neural network in Python to detect surface defects, containerised the model with Docker, and deployed on AWS Lambda with Step Functions for orchestration. Results were logged in DynamoDB and S3 with annotated images, and system performance monitored through CloudWatch. Achieved over 70% classification accuracy and validated deployment on industrial Mini-PC hardware.