📊
Live Dashboard
Market snapshot cards for top gainers, losers, most active stocks, volume shockers, breakout watch, and sector overview.
🚀 Beta Release / Public Preview
StockIndia-AI Version 1.2 Release Notes
StockIndia-AI is now available as an early public preview for educational market research, AI-assisted stock analysis, watchlist tracking, portfolio review, charting, news intelligence, and historical prediction tracking.
What is included in this release?
This release includes the core StockIndia-AI experience across dashboard, analysis, portfolio, watchlist, charts, news, and history modules.
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Fast Scan
Quick live-data-only scan for faster market screening without full ML/fundamental processing.
🧠
Deep AI/ML Analysis
AI/ML-assisted scoring with target estimates, confidence labels, risk indicators, and history save support.
🎯
Best Buy Analysis
Filtered stock review table with expected upside, risk rating, target, stop loss, R:R, and confidence information.
📰
News Intelligence
Market and stock news with sentiment scoring and buy-action style summary cards.
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Portfolio & Watchlist
User-specific watchlist, portfolio tracking, position insights, allocation charts, and risk summaries.
⚠️ Hosting Notice — Free Render Server
StockIndia-AI is currently hosted on a free Render environment for beta testing and public preview. Because this is not a production-grade paid instance, the first load can be slow after inactivity. Render documents that free web services can spin down after 15 minutes without inbound traffic and may take about one minute to spin back up when a new request arrives. Learn more from Render Docs.
- First visit after inactivity may show a loading delay.
- Page refreshes and data requests may be slower during cold starts.
- Large AI/ML analysis runs can take longer on limited free server resources.
- This beta hosting setup is intended for testing, demo, and feedback collection.
Financial Data Availability Notice
Some company financial fields can be unavailable, delayed, incomplete, or returned as zero depending on provider coverage and server conditions.
Why some financial data may be missing
- Some companies have incomplete or delayed public financial data from third-party providers.
- Free/public market-data sources can return partial responses during high load or temporary restrictions.
- Recently renamed, migrated, or changed tickers can have limited historical or fundamental coverage.
- Free server resource limits can slow down large data-fetching operations.
Fields that may be affected
PE RatioForward PEPEG RatioPB RatioEV/EBITDAEPSDividend YieldMarket Cap52-week valuesFundamental target
Known Limitations
This beta version is stable enough for preview and research, but the following limitations should be expected.
1
Cold start delay
The free Render server may take time to wake up after inactivity.
2
Deep AI/ML run time
Deep analysis performs multi-stock scoring and model processing, so it can take longer than Fast Scan.
3
Partial financial fields
Fundamental data depends on third-party provider availability and may be incomplete for some symbols.
4
News source dependency
News sentiment depends on available RSS/news results and may not cover every stock equally.
Educational Disclaimer
StockIndia-AI is built for educational and research purposes only. The application does not provide financial advice, investment recommendations, or guaranteed predictions. AI/ML outputs, confidence scores, target prices, stop-loss levels, risk ratings, and stock signals are generated from available data and statistical/technical models. Users should verify all information from official sources and consult a qualified financial advisor before making investment or trading decisions.
Planned Improvements
Upcoming versions will focus on production readiness, better data coverage, and improved speed.
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Production Hosting
Move to a stronger paid hosting plan for better response time and fewer cold starts.
⚙️
Faster Analysis
Improve Deep AI/ML execution speed through caching, precomputation, and background jobs.
📚
Data Coverage
Improve fallback handling for fundamentals, ticker migrations, and incomplete provider responses.