Team 3, 3uffalo

An example of the interface a client might see when accessing our AI chatbot.
An example of the home screen that someone using our app would see.
An example of the login screen on the external client end. Internally, there may be other required authentication protocols.

Inspiration:

Solve the problem provided to us by Enterprise Center

What it does:

Compiles data into one collective database, which is then scraped by AI to ensure high-quality, accurate data, as well as provide a convenient, chatbot style interface for the user.

Challenges we ran into:

We had to discuss a lot and were initially unclear about the aim of our project, but we used our communication and collaboration skills to rise above the initial challenges.

Accomplishments that we're proud of:

Building a concise app and providing a thorough plan for the company to implement in the future.

What we learned:

Through this project we learned to balance all of our skills and each provide something new and unique to the table, ultimately culminating in a useful product that directly addresses the challenge that we were provided with.

Built With

Submitted to

PowerUpTech Tech Design Challenge 2025 SEE/CSTEP
- Winner JBL Charge 5 Speaker

Created by

I created the canva slide for the brief example of an interaction between the AI and the employee. I also presented slides 7-8, which provided the realistic process in which gata is collected and fed to the chatbot. My pitch was "There is a 3 step process to gather the data that is fed to the AI-Chatbot. First we use a webscraping tool such as brightdata to collect relevant data from other software applications that store that data to then be transported to an excel file. Now we have to address the problem of data duplication. When data is collected from funders, employee's had to manually go through the data and compare it to The Enterprise Company's dataset in order to find duplicates. The AI-chat bot considers variables such as name, age, demographic and employee affiliation. If all of those variables match with an individual between the two data sets the AI knows a duplicate is found, and then eliminates it from the data-set. After that process is complete the data is ready to be fed to the AI. This is an example of a conversation between the AI-Chat bot and the employee in which the employee is prompting the AI to generate a report for a funder. The AI scours its dataset of templates to find the preferred template for that funder and generates a filled in report for the employee to send to the funder."

blacktea016
Annabelle Kemmer
Daijaa
Quinn Hagler
Kali Bakal99
Cassidy Shafer

Updates

blacktea016 posted an update — Jun 27, 2025 09:56 PM EDT

I want to give an update that we won the hackathon for the Enterprise company's problem statement. Reach out to me on LinkedIN for more information! https://www.linkedin.com/in/paris-riana-campbell-66ba842a8/

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Annabelle Kemmer started this project — Jun 27, 2025 11:13 AM EDT

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