AI Strategy for Businesses

An AI strategy answers three questions before any deployment: where AI will create the most value in your business, what the prerequisites are in data, skills and infrastructure, and what ROI you can realistically expect. We therefore start with a maturity audit that evaluates your data, processes and organization across 40 criteria. Each identified use case is then modeled for ROI under three scenarios and prioritized by impact and feasibility. The result is a 12-month roadmap with measurable quarterly milestones.

The investment depends on the scope: the number of use cases to evaluate, the complexity of the systems to integrate and the volume of data to audit. That is why we do not quote a standard amount before measuring your situation. The AI maturity audit is precisely that first scoping step, since it assesses your organization against 40 criteria. You then receive a phased, costed proposal aligned with the 12-month roadmap.

No platform wins on every front, because each one makes different trade-offs between performance, cost, data sovereignty and quality of support. So we run an objective benchmark of the market's solutions (OpenAI, Google, AWS, open-source alternatives) against your own criteria rather than generic rankings. Integration with your existing systems weighs as much in the evaluation as raw performance. You end up with a documented comparison that grounds the vendor selection and feeds into your deployment roadmap.

We build Law 09-08 compliance in from the design stage of your strategy, because fixing a non-compliant use case after deployment costs more than framing it upfront. The governance framework built with you covers the data usage policy, the model validation process, bias management and ethics. Data sovereignty also counts among the vendor selection criteria. The documentation of algorithmic decisions and their traceability are part of the deliverables.