Case study · Management reporting
Issues flagged the day they happen, not a month later.
The agent analyses performance and transactions, writes the report, and sends every board member their copy automatically. Issues that used to surface a month later in the report are flagged in real time.
- Real timeissue flags, instead of next month's report
- Autoreport sent to every board member
How it works
- Sales and transaction data flow into the agent.
- The agent analyses them and writes one report.
- Every board member gets their copy automatically.
- An unusual spike is flagged the day it happens, not in next month's report.
Source
Sales
Source
Transactions
AI agent
Analyses and writes
waitingReport
One report
waitingBoard member 1
waitingBoard member 2
waitingBoard member 3
waitingSource
Sales
Source
Transactions
AI agent
Analyses and writes
waitingReport
One report
waitingBoard member 1
waitingBoard member 2
waitingBoard member 3
waitingDaily sales
FLAGGED NOW: UNUSUAL DROP
NEXT MONTH'S REPORT
Before and after
Before
- Reports were put together by hand each month.
- Problems showed up a month after they happened.
After
- The agent writes the report and sends it out.
- Unusual numbers are flagged as they happen.
What we built
- Data analyst AI agent
- Sales and transaction connection
- Automatic board reports
- Real-time issue flags
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