AI dashboards and reporting
Dashboards that answer the next question too
A dashboard nobody opens is a screenshot with a hosting bill. We start from the decision you are trying to make, then build the fewest screens that support it.
The short answer
An AI dashboard combines live business data with a language model that can explain changes and answer follow-up questions in plain English. It works only when the underlying numbers are reliable, so the data layer comes before the charts.
What this stops
- A day spent assembling the weekly report
- Two systems disagreeing on revenue
- Finding out about a problem at month end
- Paying for reporting tools nobody logs into
What we build
What this looks like in practice
- Financial dashboards
- Live visibility into margin, cash, and job costing.
- Marketing and SEO dashboards
- Multi-brand views of visibility, leads, and spend. One of ours runs across five brands.
- Operational status pages
- A read-only page that tells you if your systems are healthy, from the systems themselves.
- Scheduled briefings
- A morning summary by text or email, so the dashboard comes to you.
The rule on this one
Every AI-written explanation links to the numbers behind it. If the model cannot point at the data, it does not make the claim.
Questions
What people ask us
Often built alongside
Do we need a data warehouse first?
Not always. For one or two sources we can often read directly. Once you are combining several systems or need history, a small database you own pays for itself quickly.
Can AI explain why a number changed?
It can draft an explanation by comparing the data, and it is useful for that. Treat it as a first read. We show the supporting rows so you can check it in a click.
What tools do you use for dashboards?
Usually a custom Next.js app on Postgres, because it is fast and you own it. If your team already lives in Looker or Power BI, we will feed those instead.
Tell us what is eating your week
A free discovery call with a solutions architect, or a blueprint in about a minute.