Signal mapping
Every marketing signal that matters, search, paid, lifecycle, revenue, mapped to a single canonical model.
Services / Strategy
Marketing decisions on owned intelligence.
A dashboard shows you charts. An intelligence architecture defines what every number means, where it came from, and which decision it serves — modeled data marts, canonical metric definitions, and a decision layer, designed as one system. Here’s the difference, and what the designed system contains.
What's included
IncludedArchitecture, not dashboards.
Every layer is designed to be explainable, extensible, and yours, no black boxes, no per-seat ransom.
Pipeline blueprint
The architecture for ingestion and transformation — what flows where, how it’s modeled, what “correct” means. The plumbing itself is built in data pipelines.
Decision layer
The views, alerts, and models leadership actually uses to allocate budget and set direction.
Sovereignty plan
A migration path off rented analytics toward infrastructure you control and can audit.
How it works
Designed around your decisions.
We start from the questions you need answered, then build backward to the data.
01
Blueprint
Stakeholder interviews and systems mapping produce a full architecture blueprint before anything is built.
02
Build
Pipelines, models, and interfaces are constructed in the open, documented, tested, and handed over with training.
03
Operate
We run it with you until your team is self-sufficient, then step back to advisory or fully hand over.
Before you build.
Questions, answered.
How is this different from buying a BI tool? +
A BI tool visualizes whatever data you point it at — garbage in, prettier garbage out. An intelligence architecture defines the canonical meaning of every metric first, then decides what deserves a dashboard. We don’t implement BI tools as a service; we design the system they should have been pointed at.
Do we need to rip out our current stack? +
No. The architecture wraps and extends what you have, replacing rented pieces only where ownership pays back.
Who owns the system? +
You do, code, data, documentation, and credentials transfer to you. That's the entire point.
What does it run on? +
Google-native infrastructure where possible (BigQuery, Looker, Apps Script) plus open components you can host anywhere.
Make the next move yours.
Tell us where it breaks.
60 questions · 10 infrastructure domains · 12–15 minutes · 0–100 score with prioritized recommendations. Next: data pipelines and contact.