ds@mcpanalytics.aiEmail your data and your question and get an answer about your own data, with the method shown.Email your data and question. Get an answer.
When insights are on, each card carries an interpretation written from the computed card values. The AI explains what the statistics found. Read the words next to the card, and check them against the numbers shown.
Raw numbers alone rarely tell the business story
p-values, confidence intervals, R² scores: what do they actually mean for your business?
Turning statistical output into a summary for a manager takes time.
Reading model diagnostics and assumption checks takes statistical training.
Every report card has a "back" with plain-English insights
High-level takeaways that anyone can understand. Key findings as short bullet points.
What the numbers mean, with model performance explained in plain words.
Suggested next steps based on the analysis. You decide which to act on.
Every card has a front (data) and back (AI insight). These four cards are an illustration: the figures belong to an invented churn model, not to any customer. For a real report, open the live attrition report.
| Variable | Impact | Sig |
|---|---|---|
| Contract Type | +0.824 | *** |
| Tenure | -0.512 | *** |
| Monthly Charges | +0.234 | ** |
Insights are on by default for the analyses you run; the example cards above are illustrative
From raw output to actionable intelligence
Run an analysis through the chat interface or API. Insights are on by default.
AI reads each card's computed values and writes the key findings, an interpretation, and suggested next steps.
Flip any card to see the AI interpretation. Share reports with stakeholders who don't speak statistics.
Control insight generation through the API. The generate_insights option turns it on or off per analysis; it defaults to on.
generate_insights=true turns on the AI interpretation (the default)
# Illustrative call shape, not run here tools_run( tool_name="classification_binary", taskList={ "inputs": { "dataset": "uuid://your-dataset", "target": "churned", "predictor_1": "contract_type", "predictor_2": "tenure" } }, generate_insights=True # AI insights enabled )
Upload a dataset, run an analysis, and flip the cards to read the interpretations.
Where to start
One email with your data and your question. We take it from there.
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