The problem Project Annapurna solves

We found that there were tonnes of food wasted every single day during the Indian wedding functions. In the contrast, there were lakhs of people across the nation struggling for one meal. We found that there were NGOs that were more than willing to help and the organizers of the wedding function were equally willing enough to donate all the extra mass-produced food.

We, the team Annapurna saw this unsolved puzzle with pieces scattered here and there. We used our capacities to create a one-stop solution for the users(organizers of the wedding functions) and NGOs.

Herein, the NGOs log in and provide extensive details of their previous experience, the scale of work with the conventional details of the contact, and brand-specific information.
With thousands of NGOs listed down, the user can simply filter out the most relevant ones to start a conversation. Following the outcome of the conversation, the NGO can reach the spot after the completion of the program to collect the food bulk to further distribute it amongst the needful.

Challenges we ran into

Being non-proficient with the back-end, we weren’t able to store the data submitted by the user in real-time. Had this been done we could work out a fully functional and operational project.
We also felt that the knowledge of Machine Learning could have worked out a long way to understand how to optimally suggest NGOs to the users based on more filter options and understanding the pattern in the behavior of the previous users.