/ PLATFORM
norami
It starts with a question.
Meet the data analyst for real operations. Ask your files and databases in plain language, then follow every answer to its source.
[ 01 CONTEXT ]
norami finds the meaning behind your question.
A question about harvest, inventory, or margin starts with the terms your team actually uses. norami narrows the context to the relevant sites, periods, and measures.
Your workspace and permissions determine what can be included before an answer is assembled.
Good morning, Maya
SUGGESTED
[ 02 SOURCES ]
Then it goes to the data that can answer it.
Spreadsheets, ERP exports, and connected databases can all be part of the same question. norami works with the relevant sources, rather than making your team reconcile another copy by hand.
Every source stays identifiable throughout the run.
[ 03 ANALYSIS ]
Complex work becomes a clear calculation.
norami turns a plain-language question into the steps needed to answer it: filter the right records, join what belongs together, and calculate the result.
You can open how the answer was produced, the datasets it used and the steps it took, instead of taking a confident sentence on trust.
UNDERNEATH
[ 04 ANSWER ]
One answer, ready for the next decision.
Ask for the number, a comparison, or a chart. norami brings the result into a conversation your team can continue, with its evidence still attached.
Key findings
- Site 01 is 2.6% below plan (−2.6%)
- Site 07 is 2.5% below plan (−2.5%)
- Site 04 is 5.2% ahead of plan (+5.2%)
Today at 10:42 · 18.3s
[ 05 PROOF ]
Every answer can show its work.
A useful answer tells you which assistant answered, what data it used, the steps it took, and how fresh that data was.
SEE IT ON YOUR DATASites 01 and 07 are the two at risk this cycle.
The datasets used for this answer range from Sep 12, 2026, 9:14 AM to Sep 17, 2026, 3:02 PM.
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