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Use cases

Asked once. Then it runs every week without you.

Pick a team and see the question they actually ask, what comes back, what it does about it, and the automation it leaves behind, with the ceiling that team set on it.

Retail and D2C

Ask your revenue anything

Connect the orders database and the pricing sheet. Leadership asks questions in plain language instead of waiting for analyst queues.

Which regions drove growth last quarter, and was it volume or pricing?

South led with 23 percent growth, and it is a volume story: orders rose 31 percent while average order value dipped 6 percent on festival discounts. West grew 11 percent on pricing alone. I would watch North, where both volume and price fell.

South
West
East
North
Illustrative conversation. On your data every answer carries sources you can open, and every query is read-only.
  1. AnsweredGrowth split into volume and price by region, with North flagged as the one falling on both
  2. ActedBuilt the regional canvas and set it to refresh every morning
  3. WatchingNothing was changed. This one only reads.

Ninety seconds, 19 credits. The same question took the analyst queue three days.

And then it keeps running

“Summarise last week’s revenue by region, split volume from price, and flag any region falling on both. Refresh the regional canvas and draft the note to the leadership channel.”

Every Monday 07:00Ceiling: ask before acting
Connects toPostgreSQLGoogle Sheets
Doing the workLive SQL analysisCharts in chatPin to dashboard
Try it in the demoRun it on your data

What holds it together

The answer is the easy part. The follow-up is not.

Every scenario above ends the same way: someone decides something. Insighter records that decision behind the summary you asked for, then uses the data to answer whether it was implemented and whether it worked.

Agreed, happened, and worked are three questions
A decision can be approved, never enacted, and therefore have no effect. Reporting that as one status is how a memory system starts lying, so Insighter keeps three.
Nobody fills in a form
Records are created from the analysis you were already doing. A capture step people have to remember is a capture step that does not happen.
Unimplemented decisions go quiet
Monitoring the assumptions behind a policy nobody applied would generate confident warnings about a fiction, and teach everyone to ignore alerts.

Consolidate the night shift at North hub

Recorded 3 March from the answer you asked for

Agreed

approved

Happened

not detected

Worked

inconclusive

night_shift_countflat
utilisationflat

The leading number never moved, so this was probably never enacted. Its alerts stay quiet: warning you about a policy nobody applied is how a system teaches you to ignore it.

A real decision record, six weeks after it was made.

Your data

Never used to train a model. Never sold. AES-256 at rest under a key derived per organization, so no other tenant's key opens yours, and no standing internal access to any of it.

How it is enforced

Yours is probably on the list

And if it is not, bring the question anyway. Answering it against your own data is usually enough to know.

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