At MicroStocks, we believe in radical transparency regarding how we use Artificial Intelligence. The financial markets require precision, not poetry. General-purpose AI models often suffer from "hallucinations"—confidently inventing facts or financial advice when they lack data. Our architecture is explicitly designed to prevent this by separating data retrieval from data synthesis.
Data First, AI Second
Our system does not ask an AI to "predict" stock prices or "guess" earnings. Instead, our backend pipelines pull raw, deterministic data directly from reputable, primary endpoints:
- NSE & BSE Public Feeds: Live price action, volume data, and corporate announcements.
- Regulatory Filings: Financial statements, annual reports, and shareholding patterns (including promoter pledging).
- SEC EDGAR: For cross-border dependencies and global macroeconomic context.
- Institutional News Wires: Real-time headlines from verified business media (e.g., Reuters, Bloomberg, local Indian business press).
The Multi-Agent "Committee" Architecture
Once the hard data is collected, it is passed into our specialized Multi-Agent Architecture. Rather than relying on a single AI model, we simulate an institutional trading floor:
1. The Quant Desk
Analyzes strictly numerical data—moving averages, RSI, volume spikes, and standard deviations. It has no access to news or narratives.
2. The Fundamental Desk
Evaluates balance sheets, P/E ratios, debt-to-equity levels, and cash flows to determine intrinsic valuation and accounting health.
3. The Macro Desk
Ingests sentiment from our fine-tuned FinBERT models and aligns stock-specific data against broader sector flows and institutional buying (FII/DII).
4. The Risk Manager (CIO)
Takes the outputs from the three desks, resolves contradictions, calculates a conviction score, and generates strict invalidation levels.
Strict "No Hallucination" Guardrails
To ensure E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) compliance, we utilize Strict Pydantic Outputs. The AI agents are technically constrained and can only output data in pre-defined JSON structures. If the underlying data is missing (e.g., a newly listed company has no 200-day moving average), the agent is hard-coded to return "N/A" rather than guessing.
Not Financial Advice
The AI verdicts generated by MicroStocks are data synthesis tools, not personalized financial advice. They represent mathematical probabilities based on historical patterns and current data. Always consult a SEBI-registered financial advisor before making any investment decisions. Read our full Terms of Use and Privacy Policy.