The problem DocuBot solves

Problem Statement: Deciphering the Digital Maze

In the vast online landscape, users frequently encounter a common problem – comprehending the terms and conditions of untrusty websites, risking their precious data privacy. These lengthy, complex documents often remain unexplored due to their daunting complexity.

Additionally, the boundless sea of information on the internet, spanning intricate research topics, government materials, and extensive encyclopedias, can overwhelm users. They yearn for a solution that not only simplifies these complexities but also personalizes the experience.

Enter DocuBot: The Digital Guide You've Been Waiting For!

Imagine you're surfing the web and come across a website with terms and conditions as convoluted as a treasure map in a foreign language. You're unsure if your data is at risk, and you certainly don't have the time or patience to decode it. Or picture yourself trying to understand a complex research paper that reads like an alien manuscript.

This is where DocuBot shines! We are on a mission to empower users to navigate the digital realm with confidence. With DocuBot, users can simply upload these perplexing documents and receive simplified, user-friendly explanations, ensuring their data privacy remains intact.

We aim to bridge the gap between users and the immense wealth of online knowledge. Think of DocuBot as your personal tour guide through the digital maze, making online content accessible, understandable, and tailored to your needs.

Join us in our quest to transform digital literacy, safeguard online privacy, and offer a clear path to knowledge in a user-friendly and interactive manner. With DocuBot, understanding the web has never been easier!

So, whether it's deciphering perplexing documents or making complex topics as simple as a children's story, DocuBot is your digital companion, ready to serve your needs. Upload, ask, and let DocuBot be your beacon in the digital maze.

Challenges we ran into

Our main challenge was to feed the context to LLMs based on similarity to optimize the token ussage per requests
this issue was solved by using langchian and openai