ai-analyst

To get charts and slide decks from plain-English data questions, you use a tool that parses your query, runs cohort analysis and forecasting against a connected dataset, and outputs SWD-style visualizations with stakeholder-ready Marp slide decks.

Cohort analysis in product analytics groups users by shared characteristics to track metrics like churn over time, and can be fully automated by asking a plain-English question to generate validated findings and supporting trend visualizations.

Yes, you can generate stakeholder presentation decks directly from your dataset by querying in plain English, which triggers automated creation of Marp-powered slide decks containing validated findings, confidence scoring, and formatted charts.

Yes, a connected dataset is required to perform forecasting and metric definition, as the structured analytical pipeline needs underlying data to coordinate sub-skills and generate validated findings, charts, and narratives.

The best way to visualize revenue drop drivers without writing queries is to ask a plain-English business question, which automatically generates SWD-style charts, heatmaps, and structured narratives explaining the underlying metrics.

Yes, automated data analysis works with experiment design and stakeholder communication by coordinating specialized agents through a pipeline that translates raw metrics into actionable insights, confidence scores, and presentation-ready slide decks.