Everything you need to understand a dataset
From the first upload to a downloadable executive report, here is what runs under the hood, all grounded in deterministic computation.
Automatic profiling
Row/column counts, dtype inference, semantic column mapping, and a per-column quality profile the moment you upload.
Data quality scan
Missing-value severity, duplicate detection, constant and high-cardinality columns, and IQR-based outlier flags.
Business metrics & EDA
Revenue, margins, top categories/products, trends, and seasonality. All are computed deterministically in Pandas.
Trends & correlations
Period-over-period movement, volatility, anomaly points, and a Pearson correlation matrix with strong-pair detection.
Prediction & model evaluation
An optional Ridge / RandomForest model with a real held-out evaluation using R², RMSE, MAE, or accuracy and F1.
Explainable AI (SHAP)
Global feature importance and plain-English explanations so a prediction is never a black box.
Data-leakage analysis
Flags suspicious near-perfect correlations and target leakage, with financial scale-effects handled correctly.
Compact, de-duplicated report
A 1–2 page HTML/PDF with KPIs, charts, recommendations, and XAI. Every fact appears exactly once.
What's inside the report
Concise by design and free of repeated content.
Dataset snapshot
Filename, shape, detected type, and the important columns.
Key metrics
The headline KPIs are surfaced once and never repeated downstream.
Data quality
Quality score, missing values, duplicates, and the top warning.
Important insights
The highest-signal findings, ranked and de-duplicated.
Charts
Up to two auto-selected visualisations with takeaways.
Model performance evaluation
R²/RMSE/MAE or accuracy/F1 with a plain-English read and leakage note.
Recommendations
At most three concrete, prioritised next steps.
Explainable AI
SHAP feature importance always appears in the final section.
Works fully offline in Mock mode with no API keys. the LLM is optional and only refines wording.