Integrating AI and Cloud Infrastructure for Enhanced Asset Management

Gluu is in the process of enhancing its technological infrastructure to streamline operations and improve asset management. The project involves updating an Amazon EC2 instance to support the integration of advanced AI models and cloud services. The primary goal is to integrate the Dify Bot into Supabase for efficient data management and Vercel for a responsive front-end interface. This integration will facilitate real-time learning and condition reporting for Gluu's real-world assets, leveraging a Multi-Modal AI model. The project aims to provide learners with hands-on experience in cloud computing, AI integration, and front-end development, applying their classroom knowledge to solve real-world problems. Key tasks include configuring the EC2 instance, setting up the Dify Bot, and ensuring seamless communication between Supabase and Vercel.

Enhancing Peer-to-Peer Rental Transactions for Gluu.Repair

Gluu.Repair is transitioning from Version 1 to Version 2, aiming to enhance its Peer-to-Peer Rental Feature. The current system allows users to share specific collections with clients, but lacks a streamlined process for clients to select items, choose rental durations, and view the total value of their rental requests. The project focuses on designing a comprehensive transaction flow that addresses these gaps. Key tasks include developing a user-friendly interface for clients to select items and rental periods, integrating a system to display the total rental value, and creating a seamless approval and payment capture process. The goal is to ensure a smooth and efficient rental experience for both users and clients, aligning with Gluu.Repair's organizational change objectives.

Interactive Dashboard for Image Recognition Insights

The goal of this project is to develop an internal dashboard for Gluu's Image Recognition LLM using Supabase and Vercel. This dashboard will provide valuable insights into the usage patterns and learning processes of the model, facilitating human-in-the-loop validation. The project involves mapping new KPIs and timestamps to present findings effectively. By leveraging tools like RETOOL and POSTGRES, the team will create a user-friendly interface that allows stakeholders to visualize data and make informed decisions. The project will enable Gluu to enhance its understanding of model performance and optimize its image recognition capabilities. - Develop a dashboard using Supabase and Vercel. - Integrate human-in-the-loop validation features. - Map and display new KPIs and timestamps. - Utilize RETOOL and POSTGRES for data management. - Enhance insights into model usage and learning.

Identify potential opportunities for Gluu to provide valuable solutions and data insights.

This project focuses on exploring the strategic direction and potential growth avenues for the Gluu platform, beyond the immediate development of its Agent to Agent, Google Protocol. Our current success lies in providing robust item documentation and accurate insurance valuation services. Furthermore, our advancements in Artificial Intelligence are promising and integral to our future vision. This initiative specifically aims to leverage our existing user retention model and current use cases to deeply understand the trajectory of the entire Gluu platform. We will be considering various potential business segments, one of which could involve engagement with academic institutions and specialized programs.