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Data dashboards and business intelligence

Dashboards that turn scattered data into one decision-ready screen.

We bring data that sits across different systems into a single dashboard and turn it into automated reports. Our Chura AI, AnalyzMail AI and PulseIQ case studies are working examples of this approach.

Data visualisationLive dashboardsScheduled reportsPDF exportRole-based views

What we deliver

Data pulled from multiple sources into one dashboard
Views that change by role
Automated periodic reports (email / PDF)
Threshold and anomaly alerts
Historical comparison and trend views

Is this service right for you?

Someone prepares the weekly report by hand in Excel
The same question gets two different answers from two systems
You have to ask a person to find out a number
You make decisions on intuition rather than data
You have data but nobody looks at it — because looking is hard

A dashboard is not a pile of charts

The measure of a good dashboard isn’t how many charts it holds but how many seconds it takes the viewer to make a decision. So we start from questions, not charts: which three questions does the person looking at this screen want answered? The dashboard is built around those three; everything else moves to a second level.

The second principle is separation by role. The field team, the manager and finance don’t need the same screen; the same data produces different views so each can make their own decision.

We take the data from wherever it lives

Data sourceWhat’s requiredTime
Your existing databaseRead-only access1–2 weeks
Third-party system with an APIAPI key and permissions1–3 weeks
Excel / CSV filesA consistent file format or an upload screen1–2 weeks
System without an APIAn export flow or an integration layer3–5 weeks
Several sources combinedA shared identity field (customer, order no, etc.)4–8 weeks
80%
In dashboard projects most of the work isn’t visualisation — it’s cleaning the data and matching it across sources. When scoping, the real question isn’t "which charts" but "how do we match the same customer across these two systems".

Report automation

Automated reporting usually sits alongside the dashboard: a one-page summary emailed to the manager every Monday morning, a monthly PDF management report, or an instant alert when a threshold is crossed. This removes the "forgot to check the dashboard" problem — the report finds the user.

Frequently asked questions

Our data is scattered — can you still build a dashboard?

Yes, and this is the situation we meet most often. Bringing data from different systems and files into one dashboard is a normal part of the work. What matters is that a shared identity field exists across sources — a number or code that lets us match the same customer in two systems. If none exists, defining one is the first job.

How long does a data dashboard take?

A dashboard fed by a single existing database is ready in 1–2 weeks; one fed by third-party systems with APIs takes 1–3 weeks. Combining several sources pushes this to 4–8 weeks, most of which is cleaning and matching the data.

Why a custom dashboard instead of an off-the-shelf BI tool?

Ready-made tools are good for standard reporting. A custom dashboard is the better fit when the data needs interpreting through your own business logic, when the dashboard must be embedded inside a process (seeing and acting on the same screen), or when per-seat licensing cost becomes unpredictable.

Where is the data stored?

On your own server or in a cloud account opened in your name, as you prefer. Where read-only access is enough we can work without touching your existing system at all. In every case the data belongs to you.

Which questions do you want answered?

Tell us where your data lives and which decision you want to speed up.

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