Recursive Data

FoodScanSAAS is a Software as a Service (SAAS) mobile application designed to simplify the process of understanding food items by scanning their barcodes. The app provides users with detailed information about the ingredients present in the scanned food products, along with their definitions. One of the key features of the application is its integration with ChatGPT, enhancing the user experience by providing accurate and comprehensive ingredient definitions through natural language processing.

The tool is designed to scrape data from various Ecommerce websites, including but not limited to Amazon, eBay, and other relevant platforms. The focus is on extracting information based on unique product identifiers and names, allowing users to compare prices effortlessly. The system employs web scraping techniques to fetch up-to-date information from diverse Ecommerce websites. Regular and automated data updates will ensure that users have access to the latest pricing information. This project is a powerful and efficient Real-time Ecommerce Price Comparison Tool, empowering users and buyers to make well-informed online purchasing decisions by easily comparing prices across multiple platforms. The tool’s comprehensive features and user-friendly interface aim to simplify the online shopping experience, promoting transparency and value for the end user.

The primary objective of this project was to develop an AI-based system capable of classifying text and extracting specific information in real-time from PDF files. The focus was on handling a diverse set of PDF documents, specifically contract tender filing information related to construction work. The documents were in German language, and the project involved training an AI model to classify and extract relevant data. The project successfully achieved the goal of classifying and extracting information from diverse PDF documents in real-time with 95% accuracy. The solution’s deployment on AWS EC2 with autoscaling ensures scalability, making it suitable for handling varying workloads.