What a regular dashboard gives you
A BI dashboard turns data into charts: revenue, conversion, traffic. That is useful for keeping an eye on things, but it has a hard limit — interpreting the charts and hunting for causes is still a human job, and any non-standard cut of the data needs an analyst, SQL or a report builder.
What an AI analyst adds on top
| Task | Dashboard | AI analyst |
|---|---|---|
| Show the metrics | yes | yes |
| Notice an anomaly | you have to spot it | spots it and alerts immediately |
| Explain the cause | no | investigates and writes the conclusion |
| Answer a question in words | needs SQL or a builder | plain language, in chat |
How it works
- •Pulls data from analytics, CRM, accounting and ad accounts into one picture (read-only),
- •Sends a morning summary of yesterday with comparisons against previous periods,
- •Catches anomalies and alerts straight away: a spike in bounces, a drop in conversion, overspend,
- •Answers questions like “why did margin fall in March?” — with the figures and the breakdown.
Data
Financial data is the most sensitive material a business has, so the AI analyst is installed on your server or on infrastructure you control, with read-only access that can be revoked at any moment. More on the AI analyst page, and on keeping models in-house in on-premise LLM vs cloud AI.
Frequently asked questions
Does an AI analyst replace our dashboards?
Not necessarily — they complement each other. A dashboard is good for visual monitoring; an AI analyst is good for conclusions in words and for catching anomalies early. Most teams run both.
Does it get the numbers wrong?
The arithmetic is done by code, not by the model — sums and percentages are deterministic. The model interprets the result and writes the conclusions. During rollout the reports are reconciled against your existing figures.
Our data is scattered across spreadsheets and systems — is that a problem?
No, that is the normal starting point. Whatever exposes an API gets connected directly; the rest comes in as a regular table upload. You do not need to tidy your data landscape first.