What we do
Everything starts with a question the organization cannot answer on its own.
If answering it requires building something, we support the execution. If the judgment needs to be sustained over time, we stay on the client's side. And if the question comes back every month, we turn it into an instrument. These are three ways of working, not three service catalogs.
The principle behind the three
It starts with the business, never with the technology.
Before naming a tool, we understand the business problem and the process where that problem lives. Only then is it decided which technology helps solve it, and that answer may not be artificial intelligence. When it is, it still needs to specify what type: predictive, generative, or agentic solve different problems, and treating them as interchangeable is the most common way to waste a technology budget.
It's the difference between looking for problems for a solution that was already bought, and understanding the problem until finding the solution that actually solves it. The three ways of working below are different applications of the same principle.
The point
It's the difference between looking for problems for a solution that was already bought, and understanding the problem until finding the solution that actually solves it.
Diagnostics for difficult decisions
Enter a market or exit it. Build a capability or buy it. Accept or reject an alliance. Grow, restructure, or pause an operation that already exists. These are binary, costly decisions, the kind senior leadership cannot make on a hunch.
The method builds a fault tree and pits competing hypotheses against the same evidence, instead of defending a favorite conclusion from day one. No conclusion enters the final report unless it holds up to traceable evidence. The whole process is condensed into a single working artifact senior leadership can audit session after session, one that evolves with the evidence instead of being presented complete from the start.
Halfway through the project there's a validation session with senior leadership to confirm the preliminary conclusion before developing the final recommendation. Nobody designs a growth roadmap on a question that doesn't have an answer yet.
Deliverables
- Market analysis and competitive landscape
- Root-cause diagnosis, with fault tree and hypothesis matrix
- Strategic recommendation with a 90 / 180 / 365 roadmap
Strategic advisory on technology and data
The expert counterpart on the client's side, not the vendor's side. When an organization has to govern a technology vendor ecosystem, evaluate proposals, negotiate scope, or hold the technical judgment at the table where it's decided, that function is best exercised from inside, continuously, not as a project that ends.
Independence is the condition that makes this line possible: the recommendation doesn't depend on what's convenient to sell, including the possibility of saying the right answer is to redesign a process rather than buy new technology. An integrator is not in a position to give that answer. Ladibu is.
What it looks like
- An ongoing advisory seat, with no new technology project by default
- Evaluation and negotiation of vendor proposals
- Technical judgment in the decisions the client faces every month
Data and artificial intelligence
From roadmap and feasibility analysis to data governance and execution. Strategic planning connects business objectives, processes, and organizational capabilities before committing an investment, avoiding the most common mistake: automating on top of a process that doesn't work. It isn't assumed that the answer is artificial intelligence, and when it is, it specifies whether the problem calls for a predictive model, a generative capability, or an agent that executes tasks, because each demands different data, governance, and risk.
Ladibu gets involved in the build, not just the recommendation, and leaves capabilities the client's team can sustain without depending on an external vendor. The proprietary framework, AIxBu, organizes this work into blocks that activate depending on the problem and the starting point, not as a mandatory path from start to finish.
Deliverables
- Maturity diagnosis and a prioritized opportunity map
- Solution design and a validated functional prototype
- Minimum viable product in operation, with a scale-up plan
Instruments
A diagnosis answers a question once. An instrument answers it every month, with the same discipline and without depending on someone sitting down to recalculate it. CGE, the governance of the commercial pipeline, is the evidence that Ladibu's judgment can become an auditable machine, not just a recommendation.
Next step
Let's start with the question that has no answer yet.
A thirty-minute conversation, no proposal attached.
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