Inspiration
Exploring ways to provide value to customers wanting to invest
What it does
Analyse and compile performance of a company, to give user advance information on a company based on relevant data. Uses Ai generated metrics and feeds it into our own ML model trained on previous company data
How we built it
Half the team focused on creating an agentic workflow system through the GPT API, scraped news articles relevant to company and financial sector to help evaluate different performance metrics.
Other half of the team focused on training a predictive model for a company based on metric data and previous stock information. This was followed by UI design, focusing on intuitive UX and a chat-bot like interaction style
Challenges we ran into
Understanding what is needed to accurately train a predictive model.
Learning about autogen workflows with multiple GPT agents.
Accomplishments that we're proud of
Creating a workflow that is able to analyse a company with respect to current events surrounding it and give detailed user insights.
Functional UI that facilitates interaction with financial advisor
What we learned
What's next for AI Financial Advisor
Built With
- autogen
- beautiful-soup
- django
- html
- javascript
- kaggle
- keras
- lstm
- numpy
- openai
- pandas
- python
- re
- scikit-learn
- sentence-recognition
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