Operations leadership · Business improvement · Transformation · Practical AI

Make complex work easier to run.

I help organisations untangle cross-functional operations, strengthen controls and decide where technology can genuinely improve the work. My experience spans more than a decade across regulated aviation, quality and safety, project delivery and customer operations.

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Best fitOperations leadership · Business improvement · Transformation / programme delivery · AI adoption & change

Nairobi, Kenya

ExperienceMore than a decade

Delivery scale13 mapping projects

Operating context3 countries

EducationMSc Management (AI), Distinction

CredentialCertified AI Evangelist

Selected work & evidence

Selected work, reduced to the decisions that mattered.

Three short showcases: the problem, the decision and what can be shown without exposing client or internal material.

01Operations under constraint

Making aerial-survey complexity operable.

Missions depended on aircraft, pilots, maintenance, weather, survey equipment, fuel, permits, duty limits, safety and client windows. The job was to make those dependencies visible enough to decide and act.

Scope13 large-scale mapping projects

Geography / context3 countries · 3 election cycles

Formal responsibilitiesQuality Manager · Director of Safety

GrowthFleet expanded from 1 to 3 aircraft

Responsibility

Built and maintained the quality and safety systems behind the aviation function while coordinating operations, procurement, maintenance, pilots, regulation and client delivery.

Evidence

Requirements became controlled procedures and documentation, with audits, corrective actions and risk reviews supporting follow-up as the fleet expanded from 1 aircraft to 3.

Survey aircraft on an airfield at dawn, surrounded by vignettes for crew, weather, maintenance, fuel, survey equipment, permits, timing and operating conditions. — Illustrative reconstruction of the operating logic. No client or original operational documents are shown.

02Technology readiness

Knowing when technology was not ready to operationalise.

I tested drone, photogrammetry and cloud workflows in agricultural settings. Field mapping and irrigation planning were useful; crop monitoring was not reliable enough to operationalise.

UsefulField mapping and irrigation planning

Clear inputs, a bounded question and outputs that could support a practical decision.

Not readyCrop-monitoring experiments

Limited sensors, mixed-crop conditions and inconsistent sampling made the results unreliable.

Constraint

Data quality, equipment and operating conditions limited reliability more than access to the software itself.

Decision

Keep the useful mapping and irrigation workflows; do not treat the crop-monitoring output as operationally reliable.

Agricultural drone workflow contrasting a clear field-mapping signal with a noisy crop-monitoring signal over an East African landscape. — Simplified reconstruction of the decision logic from field experimentation. No identifying farm or client information is shown.

03AI adoption & implementation

Moving the AI conversation from tools to operating questions.

My MSc and subsequent work focus on implementation: define the problem, expose missing information, assess readiness and change the surrounding process before automating it.

Academic foundationMSc Management (AI), Distinction

Internal AI programmeSelected for Foundever's inaugural AI MAXperts cohort

Professional credentialFoundever Certified AI Evangelist

Public communicationAI Backstage implementation talk

Working principle

Ask AI to surface the missing questions before asking it to produce the answer. Better implementation starts with better problem framing.

Proof of application

At Foundever, I contributed to the ideation, testing and implementation of internal AI tools through the inaugural AI MAXperts cohort. The same readiness questions now shape Elekevu process diagnostics.

View AI Backstage talk deck

Team workshop surrounded by a visual sequence from problem discovery and questions through readiness, intervention and adoption. — Simplified implementation sequence used in consulting and presentations. No Foundever internal material is shown.

What I bring

Three ways I work on complex operations.

See the whole system, make the important constraints visible and choose the lightest intervention that can actually hold up in practice.

See the whole operation

Work across people, decisions, information, controls and hand-offs rather than optimising one department in isolation.

Turn ambiguity into something manageable

Translate requirements, risks and practical constraints into clearer processes, controls, documentation and decisions.

Use technology with judgement

Treat automation and AI as interventions to evaluate, not assumptions to begin with.

Experience

A compact view of the path behind the work.

2011 to 2022Geomaps Africa / GeoAir

Management Trainee → Aviation Manager

2020 to 2022The Good Chilli

Co-Founder

2023 to 2024Swansea University

MSc Management (Artificial Intelligence), Distinction

2024 to 2026Foundever

Customer Retentions Officer · selected for inaugural AI MAXperts cohort

2026 to presentElekevu

Founder

Working style

Comfortable where the answer sits between functions.

I start with the people doing the work, the controls around them and the trade-offs hidden between teams. That approach has carried across aviation, customer operations, entrepreneurship and AI adoption.

Contact

Looking at a role, project or partnership?

Hiring & opportunitiesSee how the experience maps to a role.View CV

Projects & partnershipsBring the operating problem, not a pre-selected tool.Use the private form to start the conversation.

Across operations, business improvement, transformation, quality/risk and practical AI adoption.

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