From Ideas to Reality
Team Leader Email - acharya.rachana001@gmail.com, meghnani.bhavya@gmail.com
(FIRE) From Ideas to REality - Empowering Ideation to Adoption
Introduction In today's rapidly evolving business landscape, organizations face a significant challenge in bridging the gap between ideation and development adoption. The lack of effective collaboration and communication channels often leads to misalignment, inefficient resource allocation, and delayed project execution. To address this problem, we propose the development of an Innovation Portal—a centralized platform that leverages the power of GenAI ChatGPT model to facilitate idea sharing, problem statement drafting, ideation expansion, and project collaboration. This document presents a comprehensive case study outlining the problem statement, proposed solution, benefits, project modules, design, and architecture of the Innovation Portal.
Summary The Innovation Portal revolutionizes the ideation to development adoption process by leveraging the power of AI and collaboration. By combining the strengths of the GenAI ChatGPT model and a centralized platform, the portal enables efficient idea sharing, problem statement drafting, and collaborative project development. Moreover, it automates the creation of comprehensive business documentation and presentations, facilitating stakeholder buy-in. The Innovation Portal empowers organizations to foster a culture of innovation, accelerate project execution, and drive sustainable growth.
FIRE Portal is developed using the following technology stack: Front-End: React JS: A popular JavaScript library for building user interfaces, providing a responsive and interactive user experience. Back-End: Python Flask: A lightweight web framework that will handle the server-side logic and API endpoints, ensuring efficient communication between the front-end and back-end. AI Model: OpenAI APIs: These APIs enabling seamless integration of the GenAI ChatGPT model, allowing users to interact with the AI for problem statement drafting and module coding assistance. Database: MongoDB: A NoSQL database that provides scalability, flexibility, and easy integration with the Flask framework, storing project-related data.
Frontend - cd fire-frontend npm i --force npm start
npm run build (copy this build folder to the server and host it with any server eg. express js server)
Backend - cd fire-backend virtualenv venv pip install -r requirements.txt python main.py
Learnings: Familiarity with React JS: We have gained valuable experience in building a React JS frontend application, allowing users to add and search for ideas. This gave us the insights into creating responsive and interactive user interfaces.
Integrating GenAI Model: We have also successfully integrated the GenAI model into the workspace, providing collaborators with AI-driven assistance in curating and building idea documentation. This experience enhanced our understanding of AI integration in applications.
Python Flask Backend: Developing the Python Flask backend enabled seamless communication between the frontend and the AI model, showcasing our proficiency in creating robust server-side logic.
Working with Salesforce Admin Dashboard: Creating the admin dashboard page using Salesforce provided us with hands-on experience in working with a powerful CRM platform, gaining insights into data management and visualization.
MongoDB Database: Utilizing MongoDB as the database allowed us to store and manage project data efficiently, enhancing our skills in NoSQL database management.
Achievements:
Idea Submission and Search: We have successfully implemented the functionality for users to add and search for ideas, creating a user-friendly interface for idea management.
AI-powered Idea Curation: The integration of the GenAI model in the workspace enabled collaborators to receive AI-driven assistance in curating and building idea documentation, adding value to the platform.
Collaboration Features: Building a workspace for collaborators to work together showcased our ability to foster efficient cross-functional collaboration.
Admin Dashboard: Creating the admin dashboard page on Salesforce demonstrated our capabilities in data visualization and creating a centralized management platform.
Backend Integration: The Python Flask backend effectively communicated with the frontend and AI model, ensuring seamless data flow and smooth functionality.
Database Management: Utilizing MongoDB allowed for efficient and scalable data storage, optimizing the overall project performance.