Automated reporting: numbers from all your tools, turned into a short report your team reads

What is automated reporting?

Automated reporting is a scheduled workflow that pulls data from your business tools, calculates the numbers you track and delivers a finished report — instead of someone exporting spreadsheets and copying figures into slides. The calculations are done by ordinary code, so totals and percentages are exact. An AI step then writes a short summary of what moved and why it might matter, in plain language your team will actually read.

Do you need automated reporting?

• "Someone spends Friday afternoon exporting numbers from five tools."
• "Our dashboards exist, but nobody opens them."
• "Client reports at our agency all look the same and take hours each."
• "We only notice a drop in sales or traffic weeks after it started."
• "Different people quote different numbers for the same metric."

What do we build?

• Data collection from the tools you use, through their APIs, on a schedule you choose.
• Calculations in code for totals, changes against last period, targets and ratios, defined once so everyone uses the same numbers.
• A written summary by an AI step that explains the main changes in a few sentences, based only on the calculated numbers.
• Delivery by email, Slack, Microsoft Teams, Google Docs or Google Sheets, in the format your team already reads.
• Alerts when a number crosses a threshold you set, so a sudden drop doesn't wait for the weekly report.
• A data log that keeps each report's raw numbers, so you can check any figure later.

How does automated reporting work?

1. Collect. On schedule, the workflow pulls the latest data from each connected tool.
2. Calculate. Code computes every metric and comparison, exactly as agreed with you.
3. Summarise. The AI step receives the finished numbers and writes a short explanation of what changed.
4. Check. Sanity checks flag missing data or numbers that look wrong before anything is sent.
5. Deliver. The report goes to the people and channels you chose.

Which reports can be automated?

We start with the report that takes the most time to build by hand, then add others using the same setup.

Can you trust numbers in an AI-written report?

Only if the AI doesn't calculate them. Language models are good at explaining numbers and bad at adding them up reliably, so in our reports every figure is calculated by code and the AI step only writes the commentary around numbers it has been given.

The summary is also kept short and factual: what went up, what went down, what crossed a target. Speculation about causes is labelled as such, and the raw numbers are always in the report, so anyone can check the summary against them.

Which tools can it pull data from?

Data can come from most tools with an API. For example:

Whether a tool's data can be pulled automatically depends on its API and your plan, which we confirm during the audit.

What about data access and privacy?

The workflow uses read-only access wherever a tool allows it, so reporting can't change your data. Reports go only to the people and channels you list. If figures are sensitive, the workflow can run on self-hosted n8n, and the AI summary step can be left out or run on a privately hosted model.

How long does it take and what does it cost?

A first automated report typically takes 1–3 weeks. Setup starts at $1,000, and hosting plus maintenance starts at $200 per month. AI model usage for the summaries is paid to the provider and is usually small.

The price depends mostly on the number of data sources, how many metrics need defining and how many report versions you need. Payments are milestone-based, and the launch includes one month of free bug fixing.

When is automated reporting not a fit?

Frequently asked questions

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