Every mission starts from a concrete problem.
The problems I am brought change face, but rarely nature. Five situations come up with almost every client, and all of them follow the same path: the data cycle, the one that opens the homepage.
Each step of the cycle leads to the situation it concerns.
You are starting from scratch
A new business line, a new product, or simply nothing in place yet. The data is there, scattered across your tools, but nothing collects it, organises it or makes it available.
What I do
- I wire up collection: your new sources plugged in cleanly from day one.
- I organise the data in a structured, documented warehouse.
- I deliver the first useful outputs: dashboards, exports, indicators.
For those starting out: new activity, new product, first data brick.
Cycle steps involved
- 01 Acquisition
- 02 Storage
- 05 Delivery
The outcome
A complete chain up and running, from the first source to the first deliverable.
You can no longer trust your numbers
Every tool tells its own story: one total in the CRM, another in accounting, a third in e-commerce. Meetings open with a debate about the right number instead of a decision.
What I do
- I plug your sources into a single, automated entry point.
- I centralise everything in a documented warehouse (BigQuery, dbt).
- I model tested indicators: one KPI, one definition, one value.
For data and finance teams that want a reliable foundation.
Cycle steps involved
- 01 Acquisition
- 02 Storage
- 03 Manipulation · Compute
The outcome
A single version of every number, tested at each refresh.
Your teams lose days to manual tasks
Exports, copy-paste, files rebuilt every month, follow-ups by hand. Precious time goes into tasks a machine would do without errors or delays.
What I do
- I map the repetitive tasks and quantify what they cost.
- I automate the flows: collection, updates, reporting, alerts.
- I leave behind documented machinery your teams fully own.
For business teams that want their time back.
Cycle steps involved
- 01 Acquisition
- 03 Manipulation · Compute
- 05 Delivery
The outcome
Flows that run on their own, teams refocused on their real job.
You expect a clear ROI from AI
AI promises everywhere, but nothing that turns into results. What you are looking for: time saved, money saved, or a problem handled more efficiently than before.
What I do
- I identify the use cases and quantify the expected gain before writing code.
- I plug AI into your data: internal assistants, automations, agents.
- I ship to production and compare the outcome with the announced gain.
For leaders who want results, not demos.
Cycle steps involved
- 03 Manipulation · Compute
- 04 Augmented intelligence
- 05 Delivery
The outcome
A measured gain: time, money, or a problem solved more efficiently.
Data matters, but where to start
A clear ambition, ideas everywhere, no course set. The risk: investing in a tool before laying the foundations.
What I do
- I audit what exists: sources, tools, how teams actually work.
- I build a prioritised roadmap, with the means to match.
- I deliver a first visible result to bring the teams along.
For leaders structuring their data strategy.
Cycle steps involved
- 01 Acquisition
- 02 Storage
- 03 Manipulation · Compute
- 04 Augmented intelligence
- 05 Delivery
The outcome
A prioritised roadmap and a first deliverable that brings teams on board.