
Ketan Bhirud developed an AI-powered allergen detection API for the SafeBite_Infosys_Internship_Oct2024 repository, focusing on automated food allergen screening. He designed and implemented a Flask-based service that loads a pre-trained machine learning model and encoder using Joblib, exposing a /predict endpoint for POST requests with product data. The API processes input via Pandas, returning JSON responses that indicate detected allergens, thereby enabling downstream integration and automated testing. Ketan’s work established the core infrastructure for allergen prediction, demonstrating depth in API development and machine learning deployment, though the scope was limited to a single feature delivered within the month.
November 2024 monthly summary for SafeBite project (AabidMK/SafeBite_Infosys_Internship_Oct2024). Delivered an AI-powered allergen detection API as a Flask service that loads a pre-trained model and encoder to predict allergen presence. Exposed a /predict endpoint accepting POST requests with product details and returning a JSON response indicating detected allergens. This work lays the foundation for automated allergen screening and downstream integrations.
November 2024 monthly summary for SafeBite project (AabidMK/SafeBite_Infosys_Internship_Oct2024). Delivered an AI-powered allergen detection API as a Flask service that loads a pre-trained model and encoder to predict allergen presence. Exposed a /predict endpoint accepting POST requests with product details and returning a JSON response indicating detected allergens. This work lays the foundation for automated allergen screening and downstream integrations.

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