- Fetch demographic info using natural language (llm makes the api call based on user input)
- Create digital twin of targeted demographic
- Visualizations of spending/earning/portfolio/etc
- LLM predicts specific spending based on demographic spending/earning data + demographic data (what restaurants do they go to, what products do they buy, etc)
- Download reports (pretty PDF, but also JSON for import/export)
- Import report from JSON
- JSON import/export allows for easy sharing + no authentication required
- "Day in the life" of the digital twin
- "Price this product" for the digital twin based on demographic data + product data + market data + "what would you pay for this product" analysis from the digital twin's perspective - this is useful for marketers, bankers (financial products), fintech companies, advertisers, real estate agents, governments, small businesses who don't have the data to do this themselves
- "What if" scenarios for the digital twin where you tweak market conditions and their spending/earning/portfolio/demographics/etc. (what if they make $100k more, what if they move to a different city, what if they change my spending habits, market crashes, inflation spikes, new legislation, etc)
- Correlation insights ("spending increases when market volatility increases", etc.)
- X vs Y comparison (spending vs income, spending vs portfolio, etc.)
- Persona generation (create a story for the digital twin, describing their life, their spending, their earning, their portfolio, habits, dreams, financial goals, etc.)
- DARK MODE
- Next.js
- TailwindCSS
- TypeScript
- Shadcn/UI
- Plotly Dash
- GPT-4o
- Framer Motion
- Stocks
- Bonds
- Commodities
- Real Estate
- Cash
- Cryptocurrencies