Powerdrill AI

Chat with your data (natural-language Q&A)

Ask questions like “Which regions grew fastest last quarter?” or “What’s the average order value by channel?” and get clear answers with tables and charts. Powerdrill parses column names, joins sheets when needed, and returns results with context so you can follow the logic. Because it runs inside a data-aware workflow, you can refine prompts, filter, group, or segment on the fly—turning one-off questions into repeatable analyses without writing formulas, SQL, or scripts.

Auto visuals & smart chart selection

Skip manual chart building. Powerdrill detects data types and recommends bar, line, pie, heatmap, boxplot, and more—then formats labels, scales, and legends for readability. Save visuals to dashboards, reuse them across files, and export when stakeholders need slides. The visual engine reduces errors from hand-drawn charts and keeps styles consistent across teams, so recurring reports, ad-hoc deep dives, and executive summaries look polished without spreadsheet fiddling.

Batch analysis for big folders

Analyze at scale by dropping in large folders or many files at once. Powerdrill can process up to thousands of files totaling roughly a gigabyte, summarize each, and roll results up into comparisons you can sort and filter. This makes it practical to review multi-store sales, multi-region performance, or monthly drops without cobbling together imports. Instead of opening dozens of workbooks, you get one coherent view with drill-downs to the file level for audits and follow-ups.

Built-in forecasting & ML

Go beyond descriptive stats with time-series forecasting and pattern detection backed by classic ML plus LLM reasoning. Use presets like ARIMA, Auto-Regression, or Prophet-style models to project demand, revenue, churn, or inventory with confidence intervals. Powerdrill explains training windows and evaluation metrics in plain language and links predictions to the source series, so you know what changed and why. You can compare forecasts to actuals later and refine settings without code.

Explainable steps, exports & governance

Each run includes a readable trail: what was cleaned, which aggregations were used, and how visuals or forecasts were chosen. Export charts, tables, and summaries; regenerate with different scopes; and attach outputs to dashboards or slides. This transparency builds trust for teams that need to present findings, meet audit needs, or hand work to colleagues. Clear, repeatable steps reduce “black-box” anxiety and make it easier to maintain analyses over time.