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Qualivox Vision - Food Quality Inspection Via Computer Vision

Qualivox Vision - Food Quality Inspection Via Computer Vision

Goal

Develop an AI-powered quality inspection system that detects product defects on food production lines and provides real-time analytics to reduce waste.


Solution

The system processes images from production batches and analyzes them using AI vision models to detect defects such as shape inconsistencies, discoloration or contamination indicators. Each product is assigned a quality score and defective items are flagged automatically. The analytics dashboard provides batch-level statistics, defect trends & production performance insights.
The platform supports scalable image ingestion, asynchronous processing and historical data tracking for compliance and reporting.


Technologies

AWS EC2, AWS Lambda, AWS RDS, AWS S3, AWS SQS, AWS CloudFront, ElasticSearch, NestJS, OpenAI Vision, PostgreSQL, React, Redis, Tailwind


Team

- 1 AI Engineer

- 1 Backend Developer

- 1 Frontend Developer

- 1 QA Engineer

- 1 Project Manager

Duration

The development of this AI quality inspection system took approximately 9 to 11 weeks.