Analytics and AI dashboards built around decisions
Focused views, thresholds, alerts and AI-assisted summaries help teams see what changed, why it matters and where attention is needed.

When a dashboard is worth building.
A dashboard is useful when the source data already exists and the problem is not collection itself, but seeing change, risk and priorities quickly enough to act.
How the work takes shape.
A practical sequence keeps business rules and implementation aligned.
Name the decision
Define what someone should notice, compare or act on after opening the dashboard.
Clean the inputs
Connect sources, normalise dimensions and agree the meaning of each metric.
Build the signal layer
Design views, drill-downs, thresholds and alerts around the decision.
Add AI only where useful
Use summaries or forecasts only when the data quality and use case support them.
A clear starting point for the first version.
The price shown here is a starting estimate for a focused first version. After a short review of the task, we confirm what is included, which integrations are needed and the final cost before development begins.
Not sure whether this is the right service?
Describe the process that is causing the problem. The site assistant can point to relevant information, or you can send the task directly by email.