Platform
Xeplr Pro Suite
Four applications, built on the same open foundation and on each other. Take one, or take the set — the warehouse, AutoML and Workflow all run inside Xeplr BI, BI datasets can read the warehouse’s cubes, and AutoML’s predictions land as ordinary datasets.
Xeplr BI
Analytics, dashboards and visual intelligence
Datasets, reports and dashboards over the databases you already run, with cubes for the tables too big to query live. One model and one SQL compiler underneath all of it, so a preview and a production run cannot disagree about the same number.
Read more- Partly built
Xeplr DW
Aggregate tables for tables too big to query live
When a source table outgrows live queries, copy it into a local DuckDB replica and build a cube over it — a pre-aggregated table at a grain you choose, profiled without scanning production and sized by an exact count before anyone is told it is worth building.
Read more Xeplr AutoML
Prediction without a data-science project
Pick what you want to predict, point each input at a column you already have, and train. The prediction lands in a real table that registers itself as an ordinary Dataset — so you chart it the same way you chart anything else.
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Xeplr Workflow
Actions chained into processes that branch and wait
A workflow is a sequence of steps. Each step names an Xeplr action, binds its inputs to what earlier steps produced, and routes to the next — branching on conditions, fanning out over lists, and waiting for a person or a job before it carries on.
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What sits underneath
All four are assembled from the Xeplr OS packages — MIT licensed and published on npm. You can read the foundation before deciding whether to trust what is built on it.
See it against your own data
A demo runs on your schema, not a sample dataset. Thirty minutes, no deck.