Ingestion
Drop in instrument files; Niobia parses and checks them.
Files stream in, columns auto-map, units resolve, and outliers are flagged — messy raw exports become clean, unit-correct tables with no templating.
What this method tells you
Ingestion is one of the analytical methods Niobia AI surfaces inside the testing methods branch. The short readout is: Files stream in, columns auto-map, units resolve, and outliers are flagged — messy raw exports become clean, unit-correct tables with no templating.
Where it fits in Niobia
Niobia keeps this method connected to the surrounding workflow, so teams can move from data ingestion into adjacent methods without reformatting data or rebuilding the context from scratch.
Method-specific output, not just a screenshot
Niobia packages ingestion alongside the rest of the testing methods stack, so the result stays connected to the raw inputs, the upstream context, and the next method the team needs to run.
Frequently asked
What does Ingestion help a team understand?
Ingestion sits inside Niobia AI's testing methods workflows and helps teams turn raw process, materials, or quality signals into a defensible engineering readout.
When should engineers use Ingestion?
Use Ingestion when the question is better answered by that specific method than by a generic summary: it provides the method-specific signal, tradeoffs, and context the broader workflow depends on.
What should I read alongside Ingestion?
Start with the sibling methods in the same capability branch to see how Niobia AI connects this method to the wider workflow.
