AI Data Spot Checker

Cross-validates and flags anomalies in AI-fetched financial/quant data

Problem

When using AI platforms like Qwen for stock analysis and quant learning, users found the same question answered wrong 10 times in a row — AI-fetched data is unreliable, yet ordinary users lack quick cross-validation tools, and bad data can directly mislead investment decisions.

Solution

A lightweight tool: enter a stock ticker or data point, and it automatically pulls from multiple sources, compares them, flags discrepancies and suspected errors, and returns a confidence score. Users can run a data check before acting on AI analysis.

Users

Retail investors using AI for stock/quant analysis, financial data enthusiasts, researchers validating AI output reliability

MVP

Multi-source comparison for basic A-share/US stock quotes; extract key data points from natural language questions; flag inconsistencies across sources; generate a concise validation report; browser extension or API access

Revenue

Free basic checks, premium adds more sources, historical lookback, and auto-monitoring subscription; usage-based API for quant teams

Why now

AI financial analysis is spreading fast, but hallucination and data source quality issues make results unreliable; an indie dev can start with a few free data sources for lightweight cross-validation and validate demand quickly