Problem Statement:
Traditional search methods often fall short when it comes to complex queries or confidential data. Users struggle to find relevant information quickly, as these approaches rely on rigid keyword matching and lack the ability to understand context and meaning. This results in incomplete, impersonal search results that fail to meet the user's needs, especially when dealing with sensitive or specialized data.

Our Idea:
SparkSearch addresses these pain points by leveraging advanced natural language processing and machine learning to create semantic representations of the user's own files. This enables contextual searches that go beyond simple keyword matching, allowing users to quickly find relevant information within their confidential data without the need to share it with external parties. SparkSearch empowers users to unlock the true value of their data through a personalized, efficient, and secure search experience.

Anticipated Utilization:
1)Citation Finder
2)Confidential Document Search
3Last-Minute Work At Office