Revenue

€150.0k+2.1%

Gross margin

62.4%+0.8%

Cash Burn

€78.8k-0.7%

ARR

€98.4k+1.1%
Business Intelligence Studio

Raw Data to Insights.

We connect your data sources, model what matters, and build decision-ready embedded dashboards so your team moves faster with clarity.

Decision-ready dashboards
Automation that removes manual work
Data quality checks, analysis & monitoring
AI trend radar for your industry

Services

Simple, Effective Intelligence Delivery.

We combine business context with clean data architecture so every dashboard tells the story behind the numbers.

Process

A Clear Path from Data to Decisions.

We keep delivery tight: discovery, connection, automation, and activation in measured stages.

Step 1

Discovery Call

Align on goals, urgency, data access, and what success looks like.

Typical timeline: 30-60 min

Step 2

Discover

Clarify KPIs and the decision moments dashboards must support.

Typical timeline: 1-3 days

Decision MapKPI Definition Set

Step 3

Engineer

Connect sources and build a clean model foundation your team trusts.

Typical timeline: 3-7 days

Data ModelSource Connections

Step 4

Automate

Remove manual work with scheduled pipelines, checks, and alerts.

Typical timeline: 1-2 weeks

Automated FlowsMonitoring

Step 5

Activate

Launch dashboards with guidance, training, and iteration loops.

Typical timeline: Ongoing

DashboardsAdoption Playbook

What is next

Build out your Full Intelligence Story.

These sections make it easy to expand with portfolio proofs and deeper expertise pages.

Ready to turn data into confident decisions?

Book a short discovery call and we will map your first insight win.

Financial dashboarding focus
Clean KPI governance
Automated reporting flows
AI trend monitoring
Book an Appointment

Q&A

Common BI and AI questions.

Compact answers to the practical questions companies often ask before starting with dashboards, automation, or AI.

How do I know if my company is ready for AI?

The best starting point is not the model, but the workflow. If your team repeats manual analysis, reporting, forecasting, document handling, or client communication tasks, there is usually a concrete AI opportunity to assess.

Where should we start with AI in our business?

Start with one use case that has clear data inputs, a measurable business outcome, and a low operational risk. Typical first candidates are reporting support, internal search, repetitive document work, or insight generation for management teams.

What should a good BI dashboard actually show?

A good dashboard should help a real decision happen. That means focusing on a small number of clear KPIs, the drivers behind those KPIs, and the actions a team can take next instead of displaying every available number.

Can AI improve reporting and dashboards without replacing them?

Yes. In many companies, AI is most useful as an extra layer on top of reporting: summarizing changes, flagging anomalies, supporting faster analysis, or helping teams ask better questions of their existing data.

What can be automated first in finance or management reporting?

The first wins are often data refreshes, recurring file preparation, KPI calculations, exception checks, scheduled exports, and repetitive Power BI or spreadsheet preparation steps that currently cost time every week or month.

How quickly can a BI or AI advisory project show value?

A focused advisory or discovery phase can often produce clarity within days. The fastest value usually comes from identifying one high-friction reporting process or one high-value AI use case and designing a practical next step around it.