Financial Confidence Simulator

Run 500 simulations to test the resilience of your path to financial independence under real-world market volatility.

Hello, World!

🌱 Which Season of Wealth Are You In?

Discover your current financial season—and the strategy to match.

Take a minute to write an introduction that is short, sweet, and to the point.

📈 Consistency Compound Matrix

A powerful view of how consistent monthly investments grow over time at a 7% annual return.

Start small, stay consistent. Select a monthly amount to view potential growth.

Time Horizon Future Value
10 Years—
20 Years—
30 Years—
40 Years—

Projection based on 7% annual return compounded monthly. For educational purposes only.

What does your money look like in 10, 20, 30, or 40 years? Select a monthly investment amount to instantly see the compounding impact over time. This interactive matrix turns abstract financial theory into visual, actionable insight.

Time to Financial Freedom

Estimate when you can stop working for money—based on your real numbers.

Include retirement, brokerage, checking, savings, etc.
Most common range: 6–8%
# Pseudocode for Life Event Detection Agent core class LifeEventDetectionAgent: def __init__(self): self.data_connectors = self._initialize_data_sources() self.detection_models = self._load_detection_models() self.analysis_engine = EventAnalysisEngine() self.output_handler = OutputHandler() def _initialize_data_sources(self): connectors = { "linkedin": LinkedInConnector(config.LINKEDIN_API_CREDENTIALS), "property_records": PropertyRecordConnector(config.COUNTY_APIS), "sec_filings": SECFilingConnector(), "news_api": NewsAPIConnector(config.NEWS_API_KEY), "court_records": CourtRecordConnector(config.COURT_API_CREDENTIALS) } return connectors def _load_detection_models(self): models = { "career_transition": CareerTransitionModel(), "wealth_event": WealthEventModel(), "personal_milestone": PersonalMilestoneModel() } return models def run_detection_cycle(self): """Main execution cycle for the agent""" # Fetch new data from all sources raw_data = self._gather_data() # Process through detection models potential_events = self._detect_events(raw_data) # Analyze and qualify detected events qualified_prospects = self.analysis_engine.analyze(potential_events) # Handle outputs (CRM integration, notifications, etc.) self.output_handler.process(qualified_prospects) def _gather_data(self): """Collect data from all configured sources""" collected_data = {} for source_name, connector in self.data_connectors.items(): collected_data[source_name] = connector.fetch_recent_data() return collected_data def _detect_events(self, raw_data): """Process raw data through detection models""" detected_events = [] for model_name, model in self.detection_models.items(): events = model.process(raw_data) detected_events.extend(events) return detected_events