Sherpa - Review Analyzer

Inspiration

Our inspiration for this project stems from our desire to make a positive impact on small businesses. As second-year students, we understand the challenges that businesses face in today's competitive market. Our goal is to develop a tool that will help businesses by analyzing their reviews and identifying the areas that they should focus on to improve their products or services. By providing businesses with this valuable insight, we hope to enable them to make informed decisions that will help them grow and succeed in the long run. We believe that by leveraging technology to provide these insights, we can help level the playing field for small businesses and contribute to their growth and success

What it does

The process involves employing Python to fetch and filter out unsuitable data, and subsequently utilizing Cohere AI for conducting sentiment analysis.

How we built it

Python is utilized to retrieve the data and eliminate any unsuitable information, followed by utilizing Cohere Ai to perform sentiment analysis.

Challenges we ran into

As novices in the hackathon domain, we encountered challenges in comprehending the competition's format and faced difficulty in consolidating our ideas within the 48-hour time constraint.

Accomplishments that we're proud of

Despite the time constraints, we successfully completed the backend development and implemented a system that extracts the keywords from the reviews and ranks them based on their significance.

What we learned

Through this hackathon experience, we gained valuable skills in teamwork and achieved our shared objective. It highlighted the vast potential for growth and exploration in our chosen career paths. We also acquired knowledge on utilizing various APIs and conducting effective research efficiently. In addition, we discovered new tools and resources that we can leverage to further enhance the quality of our projects.

What's next for Sherpa - Review Analyzer

After the hackathon ends, we plan to continue the development of our application. Our focus will be on training the module with additional data to improve the accuracy of comment analysis and provide more conclusive summaries. With this approach, we aim to create an application that is more reliable and valuable to our users.