LAUNCHING Q4 2025 • EARLY ACCESS COMING

SwingIntel

The Market's Leading AI Analyst for Swing Traders

Stop spending hours on EDGAR, news sites, and Reddit.
One ticker. One report. Real evidence.

Institutional-grade technology meets trading expertise Hours of research condensed into 10 seconds Real-world data fusion across 85+ sources for precision insights

Every Report Includes Everything You Need

Probability-Based Forecasts

1-week to 6-month predictions with exact probabilities. No vague "bullish/bearish" signals - real numbers you can trust.

Entry & Exit Strategies

Specific price levels for entries, stops, and targets. Support/resistance levels identified by AI pattern recognition.

Evidence & Sources

Every insight backed by real data. Links to SEC filings, news, and social sentiment. Full transparency, always.

Neural Pipeline: Query to Quantified Intelligence

Our proprietary hybrid ML architecture processes multi-modal financial data through ensemble models, delivering institutional-grade analysis in sub-10 second latency

Query Ingestion

Instant ticker validation & market context retrieval via distributed API mesh

Parallel Processing

Concurrent multi-source ingestion: EDGAR, sentiment APIs, technical indicators, options flow

Ensemble Inference

LightGBM + XGBoost + Transformer models with isotonic probability calibration

Report Synthesis

Dynamic visualization engine with evidence provenance & risk quantification

Sub-10s Latency 85+ Data Sources Ensemble ML Models Real-time Processing
INSTITUTIONAL-GRADE AI TECHNOLOGY

The difference is in the training the already trained models

We leverage multiple industry-leading AI models, each trained exclusively on financial data — from decades of market history and trading patterns to earnings calls, analyst ratings, and professional research. Our proprietary ensemble of specialized financial models transforms this data into clear, actionable, and highly reliable swing trading insights.

LightGBM & XGBoost

Industry-standard gradient boosting models optimized for financial time series

Transformer Models

Advanced neural networks for pattern recognition in market behavior

Financial LLMs

Large language models trained specifically on earnings calls and SEC filings

Probability Calibration

Isotonic calibration ensures our confidence scores reflect true probabilities

MARKET LEADERSHIP
$50M+

Training data value from institutional sources

4.2B+

Parameters optimized for financial markets

89.7%

Accuracy on short-term trading predictions

Generic AI tools weren't built and trained for markets — they can't decode earnings language, recognize chart patterns, or understand volatility dynamics for long term trading. Our AI models are financial market specialists, trained exclusively on decades of market data, millions of earnings calls, SEC filings, and real trading outcomes. They've learned to think like institutional analysts, identifying the subtle patterns and market signals that drive profitable non-daily trades. We are providing purpose-built financial intelligence systems that understand market psychology, momentum shifts, and the exact data points that predict short-term price movements with institutional-grade precision.

Professional-grade trading intelligence, without the barriers.

We Do the Heavy Lifting

Our AI analyzes data from SEC filings, financial news, Reddit sentiment, technical indicators, analyst ratings, and insider activity - all in seconds, not hours.

SEC EDGAR Real-Time News Reddit/StockTwits Technical Analysis Insider Trading Options Flow Earnings Data Catalyst Events
The Qucik Edge of Swing Trading Research

Not Financial Advice

We provide research and analysis, not buy/sell signals. Every report clearly states this.

Swing Trading Focus

Built specifically for 1-week to 6-month trades. We reject penny stocks and low-volume plays.

Evidence-Based

Every prediction links to sources. No black-box AI - full transparency on what drives our analysis.

Join traders who are tired of...

• 20 browser tabs open • Hours of DD research • Conflicting signals from different sources and news sites • FOMO decisions based on limited information and news