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Function · Reporting
Artellis builds a tool that writes the plain-English brief: what moved, what is odd, what to do next.
The pain
Why this one is worth fixing
Your dashboard shows the numbers, not what changed or what to do about it. Everyone on the call sees the same chart and comes away with a different story, because nobody wrote down the honest one.
What Artellis builds
A plain-English monthly brief: what moved, what’s odd, what to do next. Written before the meeting, not scrambled during it.
How it works
- 01Pulls the dataWhatever your source of truth is: warehouse, spreadsheet, product analytics, finance.
- 02Writes the story, not just the number‘Revenue up 8%, driven by two enterprise deals. Churn ticked up, the same cohort as last month.’
- 03Suggests 3 next actionsNot a wall of insight: three things worth doing this month, tied to the numbers.
Example artefact
What the output actually looks like.
May monthly brief · draft
Written from raw data · 3 actions proposed
Revenue +8% MoM (€142k). Two enterprise deals carried the month.
Churn 3.1% (was 2.4%). Same cohort as April. Check onboarding week 2.
Anomaly: refunds spiked Tue 14 May, traced to a billing retry bug.
Actions: (1) rework onboarding wk2 (2) publish refund root-cause note (3) forecast June without enterprise tailwind.
You edit and send.
Where it plugs in
Your data warehouse / spreadsheetGA4 / Mixpanel / PostHogStripe / your billingSlack / email
Guardrails
- Human-in-the-loop: nothing sends, signs or spends without you approving it.
- Your data stays yours, hosted in your tenant or a dedicated Artellis workspace, never used to train public models.
- Week-one build: something small and useful is live in the first week, before we scope anything bigger.
FAQ
How long until we see something working?
A first working version of the reporting tool inside week one. Refinement and rollout happen after you have seen it work against your real inputs.
What do you need from us to start?
About 45 minutes to walk through the current flow, sample inputs (emails, files, screenshots, whatever you actually work from) and one person on your side who owns the outcome.
What happens if the AI gets it wrong?
Every draft goes to a human before it leaves the building. When you correct it, the tool learns your standard so the next one lands closer to right.
Bring us this workflow
One workflow. One week. Something working.

