Je construis l'architecture qui les relie, pour transformer votre savoir institutionnel en intelligence hybride.
I'm an AI strategy consultant for impact organizations. I come from the field. I know what an 85% collection rate means, how a donor project cycle works, what a MEAL report looks like. That domain knowledge is what makes the architecture I design reliable in practice, not just on paper.
I help impact organizations turn their data and institutional knowledge into usable intelligence. AI is the means. Data architecture, context engineering and automation are the tools. I audit, design, prototype and hand over. My work ends when your organization can carry it forward without me.
More about my background →I work with humanitarian and development organizations, microfinance institutions and impact finance structures. Wherever complex data and deep professional expertise are ready to be connected.
Data in silos, disconnected systems, knowledge in people's heads. I connect your internal sources, create a single source of truth and document what your organization knows before it walks out the door.
Actor reports, sector projections, public datasets, geopolitical and security data. I monitor, cross-reference and synthesize what your organization doesn't have time to read alone, to turn scattered information into actionable intelligence.
Donor reporting, project proposals, compliance analysis, blended finance deal structuring, document synthesis. Your teams decide. AI handles the heavy lifting.
The AI I design must be trustworthy. For your teams, your clients, your beneficiaries and your partners. Ethics isn't a constraint added after the fact. It's a design requirement.
This charter is mine. I also write yours: a custom AI ethics framework, grounded in your data and your decisions, enforceable with your partners and readable by your board.
Read the full charterSystematic Data Processing Agreements (DPAs), AI architectures designed to minimize exposure of sensitive data and reduce the risk of leaks or misuse.
No tool goes live before the teams using it understand how it works, where it can go wrong, and what its limits are. The final call always stays human.
Every solution is sized to actual need. I favor lightweight architectures and energy-efficient models, and I won't deploy tools that are oversized relative to the actual need.
Understand your data before picking a tool. Prove the use case before investing. Hand over the knowledge before stepping away.
Understanding your data, systems, processes, information flows and constraints. Mapping key processes. Identifying high-value use cases. Ruling out those that don't hold up in your reality. → Data and process map, prioritized opportunity matrix.
Designing the architecture and documenting the business context: definitions, management rules, procedures, edge cases. Turning tacit knowledge into context the machine can use. In liaison with your IT department where needed. → Target architecture, roadmap, context documentation.
One use case, a concrete tool tested with the people who will use it. Lightweight automation, dashboard, small application, security monitoring tool, proposal writing assistant, beneficiary tracking dashboard. Not a trade show demo. A prototype fed by the business context designed in phase 2 and validated in your real conditions. → Working prototype, documentation. 3 to 6 weeks.
Testing relevance, output quality, reliability, traceability. Measuring user adoption. Identifying risks and limitations. Clear recommendation: move forward, or stop. And why. → Evaluation report, go / no-go recommendation.
Training your teams on tool use, critical reading of outputs and context engineering. So they can evolve the tool when procedures change or a donor updates its requirements. Handing over documentation, methods, governance. Drafting your AI ethics charter if needed. The goal: your organization decides what comes next. → Training materials, documentation, charter, procedures. 2 to 4 weeks.
I design, prototype and hand over. I don't build production systems and I don't bill for maintenance. Your organization stays sovereign over its technology.
The numbers say it best. AI isn't a promise anymore, it's a measurable operational lever, already adopted by the organizations that moved first.
AI in impact organizations raises real questions. Here are honest answers to the most frequent ones, no jargon, no detours.
A 45-minute conversation, free, no commitment.
I send a short questionnaire beforehand, so the conversation focuses on your data, your context and your real challenges. Not on generic topics.