AI Reporting & Dashboards for Irish Businesses

What problem ai reporting & dashboards solves

Business owners in Ireland do not need another chart. They need someone to explain why last month was down, and the answer is usually buried across three systems nobody has time to reconcile.

Why businesses are looking for ai reporting & dashboards

This service sells itself to a specific person: the operations or finance lead who spends the first hours of every week exporting, pasting and formatting the same figures for a management meeting. They are not looking for analytics sophistication. They want Monday back. Where we add caution is on the numbers themselves. A dashboard makes existing data problems highly visible and highly public, so if two systems disagree today, the dashboard will broadcast that disagreement to the board. That is ultimately healthy, but it should be expected rather than discovered in a meeting. In the enquiries that reach us, almost nobody uses technical language. People describe the problem in their own words — asking for "automate our weekly management report", "business dashboard for small company", "stop building reports in excel", "live sales and jobs dashboard" and "kpi reporting without a data analyst" — and what they want back is a plain answer with a price attached.

What to look for in ai reporting & dashboards

Count the hours spent preparing management reporting each month. If it is more than a day, a delivered dashboard on your existing systems pays back quickly and permanently.

• The specific figures the management meeting already argues about, refreshed automatically
• Agreed definitions so revenue, jobs and margin mean one thing across departments
• A readable view on a phone for owners who are not at a desk
• Alerts when a number moves beyond a threshold, rather than another dashboard to remember to open

Our data is not clean enough

The dashboard will show that plainly. We scope a reconciliation step first where it is needed rather than papering over it.

We already have a BI tool nobody uses

Usually because nobody built the specific views. We can deliver into your existing tool instead of adding another.

Who updates it when we change process?

Definitions are documented and editable, and we quote a small change budget rather than leaving you stranded.

What you get

Fixed scope One-time build Hosting, new data sources and reporting nth.

• Connections to CRM, accounting, ads and analytics sources
• Reconciled metric definitions agreed with you in writing
• Live dashboard on desktop and mobile
• Natural-language question box with query transparency
• Automated monthly narrative report by email
• Anomaly alerts when a metric moves outside its normal range

Technology we use

We build on proven, well-documented platforms so you are never locked into us.

• Supabase
• Postgres
• Looker Studio
• Google Analytics 4
• Xero
• HubSpot
• Meta Ads
• OpenAI (EU)

How the project runs

Decision-first definition (Day 0–4): We start from the decisions you need to make weekly and monthly, then work backwards to the metrics. Dashboards built from available data rather than needed decisions end up unused. Metric definitions in writing (Day 5–9): Every metric gets a written definition and an owner. Half the disagreement in reporting projects comes from two people meaning different things by the same word, such as an active customer or a won job. Source connection and validation (Day 10–18): Data sources are connected and each figure is validated against a known-correct manual count. A dashboard that is subtly wrong is worse than no dashboard, because decisions get made from it. Layout and narrative build (Day 19–25): The dashboard is laid out so the most important number is unavoidable, with plain-English commentary that explains what changed and why rather than leaving interpretation to the reader. Alerting on thresholds (Day 26–29): Thresholds are set so genuine problems push a notification to you. Nobody checks a dashboard daily forever, so the important movements have to come and find you. Quarterly relevance review (Ongoing): Every quarter we remove metrics nobody used and add what has become relevant. Dashboards accumulate clutter, and pruning keeps them being read.

What we have learned delivering ai reporting & dashboards in Ireland

The most common failure is a beautiful dashboard nobody opens after the second week. Starting from the decisions rather than from the available data is the only reliable fix we have found for that. Written metric definitions prevent an argument that otherwise arrives at the worst moment. When a figure is challenged in a board or bank conversation, the definition and its owner should already be documented. AI narrative summaries are useful for explaining variance, and we keep them tightly bounded to the underlying figures. Commentary that speculates beyond the data undermines trust in the numbers it sits beside.

Measured outcomes

1 place All numbers — Sales, marketing, finance and operations reconciled in one view. Monthly Auto narrative — A written explanation of what moved, generated from the data. Ask In plain English — Type a question, get an answer with the underlying figures shown.

Can I trust an AI answer about my own numbers?

Only if it shows its work, which is why every answer displays the query and the underlying rows. The AI translates your question into a query against defined metrics — it does not estimate or invent figures.

What sources can you connect?

Typically Xero or Sage, HubSpot or Pipedrive, Google Analytics 4, Google Search Console, Meta and Google Ads, Stripe and your website database. Anything with an API or a scheduled export can be included.

Is this better than Power BI or Looker Studio?

It is complementary. We often build the reconciled data layer and then surface it in Looker Studio, adding the AI question box and monthly narrative on top. The value is in the clean, agreed metric definitions underneath.

Who can see the data?

Access is role-based and enforced at the database level, so a team member only sees the metrics you assign them. All data stays in EU-hosted infrastructure with an audit log of queries.

How long does a reporting build take?

Usually three to five weeks: one week agreeing definitions, two weeks connecting and reconciling sources, then a pilot month where we check every figure against your own records before you rely on it.