Expert AI data analyst that analyzes any CSV, Excel or tabular dataset. Paste or upload data and get: 📊 Column profiling & statistics · 💡 Key patterns & anomalies · ⚠️ Anomaly detection · ✅ Data quality score · 🔗 Correlation insights · 🚀 Actionable recommendations. Works with sales, financial, survey, log, and any structured data. Educational purposes only.
Four-layer AI detection evasion, not word swapping. Real math (burstiness CV, vocabulary density) — no guessing. Detector-specific: attacks GPTZero, Originality, Turnitin by their weakest links. Chinese NLP: tracks 四字成语密度, a blue ocean. 105+ AI markers with genre-aware replacements. Research-backed (27 reports, 25+ papers). Honest: 75-85% typical improvement, no fake 100% claims.
A full analysis pipeline that turns a dataset into a finished report, not just charts. Hand it a CSV, Excel, Parquet, or JSON file and it cleans the data, scores its quality, runs EDA, and where the data supports it, trains a prediction model with SHAP attribution and a backtested forecast. You get a trust score, ranked findings, and recommendations as a Word doc, an interactive HTML report, and an optional PowerPoint deck. The numbers come from code, so they stay consistent, never invented.
Audits soccer analysis before conclusions are trusted: source tiers, dates and seasons, competition splits, 450-minute sample checks, availability flags, and uncertainty labels.
Analyzes football forecasts provided by the user to identify consensus, agreement levels, prediction ranges, and key disagreements in one structured report.
Forces AI agents to verify every factual claim through live search before output — attaching [SPECULATION] and [UNVERIFIABLE] labels to anything unconfirmed, so fabricated URLs, outdated numbers, and invented citations become visible instead of silent.
Scan AI Skills and MCP servers before installation. Detect risky scripts, permissions, dependencies, network access, credential exposure, file changes, and suspicious configurations — then generate a clear evidence-based security report.
If GA4 revenue looks off, ROAS seems wrong, or conversions don't add up, start with the tracking layer — here's the fix path. Built for SaaS and e-commerce teams, this helps you build, audit, or debug GA4, GTM, Google Ads, and Meta tracking with probability-ranked root causes, copy-paste GTM code, and a phased checklist your team can ship. Describe the symptom and get a prioritized path through broken events, missing revenue parameters, GTM gaps, consent changes, and attribution mismatches.
Know if your backtest is a real edge or overfit noise. Runs bar-permutation MCPT, Deflated Sharpe, PBO/CSCV, Hansen SPA, Romano-Wolf StepM, a stationary bootstrap and an out-of-sample split on your own returns — no market feed, no API keys.