An AI report generator that computes your numbers

Generated means a language model produced the number by predicting a plausible answer. Computed means arithmetic ran over your rows. Generated figures are usually close and occasionally precisely wrong, with nothing marking which is which. Every number in a Dashlytics report is computed; AI only writes the prose around it.

These two words get used interchangeably in this category, and they describe opposite things.

Generated means a language model produced the value. It read your data as text, predicted what a plausible answer looks like, and wrote it down. It will be roughly right most of the time. It will occasionally be precisely wrong, and there is no marker distinguishing the two.

Computed means arithmetic ran over your rows. Revenue is the sum of the revenue column. Margin is revenue minus cost, divided by revenue. The result is reproducible, checkable against the source file, and identical every time.

Everything numeric in a Dashlytics report is computed. The AI receives the finished figures and writes about them. That is the entire scope of its job, which is why it cannot invent a number.

The practical test: open any figure in the report and trace it back to your spreadsheet. It will reconcile. If a tool cannot survive that test, the report is not safe to send to a client, a lender or a board.

The input is the export you already have. Order history from a store, a deal list from a CRM, a spend export from an ad platform, a sales ledger from an accounting system: all of them produce CSV or Excel, and that is enough.

Column roles are detected from your headers, so there is no mapping screen to work through and no template to force your data into. If your file has a cost column you get margin analysis. If it has a channel and spend column you get ROAS and acquisition cost. If it has neither, the report says so rather than showing an empty section.

We have no connectors, deliberately. Every system you would want to report on already has an export button, and reading that file needs no OAuth, no permissions and nothing to maintain.

A report generator that cannot see data problems will describe them confidently. If 30% of your cost column is blank, a margin figure still renders, and nothing on the page suggests it is unreliable.

Alongside every Dashlytics report is a Data Readiness score, a rule-based audit of how complete and consistent your file is. Missing values, inconsistent categories and unparseable dates are named directly. It tells you how far to trust the report before you send it, which no other tool in this category surfaces.

Worth saying plainly rather than pretending we fit every case.

Use a document designer such as Venngage or Storydoc if what you need is a designed, narrative deliverable: your own layout, your own copy, brand styling, a persuasive structure. Those tools build the document. We build the analysis inside it.

Use a notebook or analysis tool if you want open-ended exploration, custom statistics or code you control. Our engine computes a fixed and well-chosen set of analyses; it is not a general query environment.

Use a connected BI platform if the report must refresh on a schedule from a live source, or be embedded in your own product. We read files, which means someone has to upload one.

We are the right answer when you have a spreadsheet, limited time, and you need a defensible report today rather than a data project.

The same file produces both, so this is a question of what you need to hand over rather than which product to buy.

A report is finished and fixed: a PDF you send, slides you present, a written summary someone reads once. A KPI dashboard is live and explorable: you filter it, drill into it and check it again next week. Upload once and you have both.

If you are comparing products rather than outputs, the dashboard tools page covers how this differs from a traditional BI platform, and the Power BI alternatives comparison includes when to stay where you are.