Patterns are what make data useful: sales that peak every December, customers who buy A then B, a segment that churns twice as often. Finding them by hand means building pivot after pivot. AI can test thousands of combinations quickly, but it can also find patterns that are pure coincidence.
Plumb is a privacy-first data platform. We think AI should do the tedious parts of analysis, like reading every row, spotting patterns and drafting charts, while you keep control of the questions and the conclusions. Every answer Plumb gives points back to the rows and columns it came from, so you can check the work instead of taking it on faith.
How Plumb helps: Pattern discovery
Plumb's pattern discovery scans your data for trends, seasonality, segments, correlations and changes over time, and reports each pattern with its strength and how many rows support it. Weak or tiny-sample patterns are labelled so you do not chase noise.
How It Works
These are the types of patterns Plumb looks for.
- Trends: steady growth or decline in a metric over time.
- Seasonality: repeating weekly, monthly or yearly cycles.
- Segments: groups of rows that behave differently, such as a region or customer type.
- Correlations: columns that move together, with a reminder that correlation is not causation.
- Change points: moments when a metric suddenly shifted.
Where This Helps
Sales
Find which products, regions or channels drive growth.
Customers
Identify segments with higher churn or higher lifetime value.
Operations
Spot weekly cycles in demand to plan staffing.
Try Plumb in early access
Plumb is in early access. Join the waitlist on tryplumb.pro to get an invite. Early access covers Excel (.xlsx), CSV and JSON files, and we are adding more sources as people ask for them. Your files are processed privately and are never used to train models.
Patterns worth acting on
Now you have a repeatable way to do it, by hand or with Plumb. Join the waitlist and tell us what your data looks like; we read every reply.
Join the waitlist