Inspiration

We saw an issue in the accessibility of the US social welfare system. In fact, many aspects of government paperwork are very difficult to deal with, but we saw no real solution for aiding in applications to social welfare. Therefore, we decided to fill this niche with our product.

What it does

Our user-centered AI agent works to guide users through the process of finding social welfare programs that fit their needs and support them to apply for those programs. The agent is designed to be friendly, empathetic, and very easy to interact with. It also parses the data you give it through casual conversation and uses that information to check for eligibility for different social welfare programs.

How we built it

We built this AI agent using API calls to major Large Language Models. We designed stochastic models and algorithms for eligibility checks, and we set certain guidelines for agent interactions to streamline the process.

Challenges we ran into

Some challenges we ran into was webscraping welfare program eligibility requirements, developing a dynamic system that asks essential yet effective questions, and a intuitive UI that anyone could use.

Accomplishments that we're proud of

We created a functional AI agent that is rather successful at parsing the data that we are looking for. The structure of the user agent discussion has also been designed very beautifully. The agent has very dynamic responses to user inputs and shows surprising amount of empathy to the situation that users find themselves in.

What we learned

We learned good programming protocols, incorporating large language models into software, ensuring security of private information, and gained mastery of group development through the tool of GitHub.

What's next for CareNet

We can expand the database to include more state-specific programs, improve the database update methods, and add functionality to the agent to have them provide further guidance into the process of applying for specific social welfare program.

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