The Next-Generation AI-Powered Financial Intelligence
SHAMAN filters the complexity of modern markets through artificial intelligence, transforming public disclosures, financial news, technical indicators, fund flows, and historical price behavior into decision-ready intelligence. By adapting portfolio construction to each user's risk profile and making institutional-grade analytics accessible through an intuitive platform, SHAMAN democratizes data-driven financial decision-making for first-time investors, advanced traders, and professional market observers.
Signals, forecasts, portfolio optimization, simulations, and learning move together in one product surface.
SHAMAN follows KAP filings and financial news, summarizes relevant events, and explains their possible market impact in a concise report format.
Historical prices and indicators are processed by forecasting models so users can compare model-driven scenarios before making decisions.
The portfolio engine adapts stock, gold, USD, and cash exposure according to the user's risk appetite and diversification constraints.
SHAMAN tracks ETF and fund inflow/outflow behavior to provide accumulation and distribution context alongside news and price-based signals.
Users can simulate portfolio choices, follow virtual performance, and understand outcomes before moving from analysis into real investment action.
Financial explanations and educational content are placed close to the tools so beginners can understand the reasoning behind each decision step.
Live inputs become AI interpretation, risk-aware allocation, and product-ready decisions.
SHAMAN collects KAP disclosures, financial news, historical prices, technical indicators, fund flow data, and the user's risk profile as structured system inputs.
Backend services normalize market inputs, summarize disclosures and news, score their impact, and run forecasting models to convert raw data into interpretable signals.
The risk engine uses user preferences and diversification constraints to create personalized stock, gold, USD, and cash allocations before simulation.
The Reflex interface presents dashboards, AI reports, chatbot guidance, portfolio simulation, and financial academy content as one usable web product.
Explore the completed SHAMAN experience through real application screens covering onboarding, intelligence, risk-aware portfolios, simulations, and AI guidance.
A simple account flow gets users into SHAMAN quickly and prepares the platform for personalized use.
A focused entry flow captures investor context before SHAMAN personalizes the experience.
Risk profiling turns user preferences into a practical foundation for portfolio decisions.
Users narrow the investable universe with structured filters before deeper analysis begins.
Market news is summarized into clear signals so users can react to relevant developments faster.
Market data and news are converted into concise reports with clear signals and investor context.
Ensemble forecasts help users compare future asset trajectories through model-driven signals.
Charting tools and indicators provide a compact workspace for interpreting market behavior.
Paper trading and portfolio tracking let users test strategies before committing real capital.
The AI assistant answers investor questions in context with SHAMAN's market intelligence.
Conversational guidance helps users interpret portfolio choices and next-step opportunities.
The academy module turns financial concepts into structured, accessible learning content.
This walkthrough shows the completed application in use, from AI-powered market reports and forecasting to portfolio generation, paper trading, and the financial academy.
SHAMAN does not create the same allocation for every investor. The portfolio engine adapts distribution weights to each user's risk appetite before the strategy is simulated.
The same market universe can produce different asset distributions for different people. A conservative user receives a steadier allocation, while a growth-focused user receives a more stock-heavy allocation.
SHAMAN combines a high-performance data pipeline, robust backend architecture, and modern AI tooling to convert fragmented market data into reliable product features.
Developed by a focused computer engineering team combining full-stack development, financial data engineering, machine learning, and academic guidance.
