The problem Samarpit solves

JIRA-type Planner: This feature allows NGOs to schedule their events on the platform. Multiple volunteers can participate and are matched to projects through a Smart AI matchmaking algorithm, ensuring efficient collaboration.

Marketplace for Fundraising: NGOs can create and manage fundraising campaigns, receiving donations directly through the platform. Additionally, sellers who wish to contribute to society can list their resources, providing valuable support to NGOs.

Social Media Integration: NGOs and volunteers can upload their stories and posts across multiple platforms, such as Instagram, Facebook, and Meta apps, increasing their reach and visibility.

Feedback Analysis: Utilizing the LangChain model, Samarpit gathers feedback from users and generates insightful summaries. The platform also includes questionnaires to delve deeper into user experiences and suggestions.

AI-Chatbot (Samarpit.ai): Built with DialogFlow, this AI-powered chatbot addresses all queries and ambiguities related to the campaigns and NGOs listed on the platform, providing instant assistance to users.

WhatsApp Communities: Facilitating communication and collaboration, this feature enables interactions between volunteers and NGOs, fostering a sense of unity and cooperation.

Challenges I ran into

User Experience Design: Creating an intuitive and user-friendly interface that caters to a diverse audience, including NGOs, volunteers, and donors, posed significant challenges. Balancing functionality with simplicity required extensive user testing and iterations.

Integration of Multiple Features: Combining various functionalities, such as fundraising campaigns, social media uploads, and AI-driven chat support, into a cohesive platform required careful planning and robust architecture.

AI Matchmaking Algorithm: Developing a Smart AI matchmaking algorithm that effectively pairs volunteers with suitable projects was complex. Ensuring accuracy and minimizing biases in matching required extensive data analysis and model training.

Data Privacy and Security: Handling sensitive user data, including personal information and financial transactions, necessitated strict adherence to data protection regulations and implementation of robust security measures.

Scalability: Building a platform that can handle increased traffic and user engagement as it grows was a key consideration. Ensuring that the infrastructure can scale effectively without performance issues was a significant challenge.

Feedback Collection and Analysis: Designing an effective feedback collection mechanism that encourages user participation and accurately captures insights was challenging. The integration of the LangChain model for analysis added an additional layer of complexity.