1. The ticker as a starting point
A ticker is the short symbol that identifies a security on an exchange. AInvestor uses this starting point to find the company, market, currency and classification, then keeps the same security in focus throughout the analysis workflow.
The symbol alone does not explain a business. It acts as a key for connecting available observations without confusing a company, an industry category, a fund or another instrument category.
2. Current and historical data through the latest available observation
AInvestor brings together current financial data and available historical series to show an observed position and its evolution. The latest update, reporting periods, sources and missing values help users assess the scope of the analysis.
Missing data is not invented or automatically replaced with zero. Coverage varies by security, market, period and available provider.
3. Snapshot organizes financial facts
Snapshot presents a structured company view: profile, liquidity, financial health, growth, profitability, valuation, dividends and other available observations. Indicators are educational reference points, not transaction signals.
Users can then open detailed views to understand each measure, its period and the data behind it.
4. Gauge 360 separates Metrics and Sentiment
Gauge 360 first presents Metrics: dimensions and drivers derived from observed financial data and calculations defined by the methodology. The Sentiment view separately examines the observable tone of news and the available information context.
Sentiment is neither an accounting fact nor a forecast of the next price movement. Keeping it separate avoids presenting media perception as a fundamental measure.
5. Where artificial intelligence intervenes — and where it does not
Data is first collected, normalized and connected to its reporting period. Ratios, scores and other deterministic calculations are produced separately. Artificial intelligence is therefore not tasked with inventing figures, replacing missing data with zero or hiding a missing source.
After Metrics and Sentiment have been reviewed, Core uses artificial intelligence to synthesize important relationships, drivers, risks and observable limitations. Brainier then lets users question that reading, understand terminology and adjust the educational depth.
6. The concrete result for the user
At the end of the workflow, users obtain a structured reading of the company’s current situation, historical evolution, financial strengths and weaknesses, available information context, and elements that remain uncertain or missing.
The benefit is not an opaque answer telling someone what to buy. It is a research file that is faster to build, easier to verify and reusable from one security to another. Sources, limitations and important questions remain visible so investors can form their own judgment.
7. From peers to portfolio context
Peer comparisons place a company among businesses with relevant economic characteristics. Portfolio analysis then adds weight, concentration, currency, diversification and each position’s contribution.
AInvestor therefore helps users move from an isolated security to documented thinking about all their positions while leaving investment decisions in their hands.
8. An explainable method without a buy or sell instruction
AInvestor distinguishes observed data, deterministic calculations and artificial-intelligence-assisted interpretations. Freshness, confidence, sources and missing data should remain visible.
The platform organizes and explains financial information to accelerate research and learning. It does not assess whether an investment is suitable for a person and issues no personalized buy, hold or sell instruction.