Addepto's solution aimed to detect and assess image quality. Throughout the project, our team focused on: • Efficiently detecting and evaluating image quality using cutting-edge computer vision algorithms, particularly VGG. • Constructing an advanced solution tailored to meet Teezily's requirements. This solution included a set of pre-defined quality control rules and was trained on platform-uploaded images to facilitate the quality control procedures.

We developed the Aviation Sourcing Chatbot for a U.S.-based global company specializing in organizing private flights worldwide. It simplifies ASR document creation, seamlessly integrates with the TripGrade system, and operates on AWS. Acting as an assistant, the chatbot automatically creates and submits ASR documents, ensuring efficient trip planning and accurate information gathering for optimal outcomes.

While working on the project, our team concentrated on: Developing an artificial intelligence system for airports that utilizes face recognition technology. This system aids airport personnel in confirming identities by comparing video footage with database records. The staff receives alerts if any discrepancies are detected. Creating an airport-specific chatbot powered by a large language model (LLM). This bot is constructed on a comprehensive database of airport information. It's designed to provide passengers with useful answers to frequent inquiries such as terminal locations and flight delay updates, without requiring manual input of questions.

Here's a reworded version of the project description: Addepto collaborated with a British firm to tackle the issue of simplifying bottle recycling, with the goal of enhancing user experience and efficiency. Our main objective was to create and incorporate an accurate artificial intelligence model that could identify objects inside recycling units, while simultaneously implementing measures to prevent fraudulent activities.