Data Director.Consulting

Gozem needed a coherent AI strategy spanning operations, logistics, driver management, ecommerce, vehicle financing, customer experience, and fintech, backed by a structured view of the AI vendor and tooling landscape.

Documented internal AI needs across 9 business units (Transport, Ecommerce, Financing, Finance, Data, Product, Marketing, Operations, Sales) with 50+ stakeholders contributing. Conducted a structured market scan covering 133 tools and vendors across 38 categories: AI vendors, foundation model providers, and automation platforms relevant to Gozem’s stack. Catalogued 49 validated use cases. Built an adoption framework around the 6 currently in implementation: content creation and daily assistance (near-full adoption by top management), coding and code review (rolling out with the product team), classifier and others (in use by the data team). Each use case ships with its agentic workflow architecture.

Business and operational teams alongside some external partners across Gozem’s countries lacked a unified workspace for data and AI applications with fast iteration.

Architected and led development of the Data Hub web app: data exploration environments, data-driven applications, AI-powered tools, operational workflows, and self-service analytics modules. Built role-based access governance with 3 access tiers (user, service_admin, platform_admin) crossed with 3 team roles (viewer, worker, manager), supporting 83 internal employees (63 actively using) and 261 external partners collaborating across Benin, Togo, Gabon, Cameroon, and Congo. Onboarded 2 engineers who shipped 2 additional self-service apps onto the platform.

Financing Operations team manually entered data from supplier and operational invoices in multiple formats, slowing reconciliation across Gozem’s multi-country operations.

Architected and built an automated pipeline ingesting thousands of invoices per month (PDF and image formats) using LLM-powered OCR and document intelligence. Designed an agentic workflow supporting custom schema extraction, with a validation layer flagging anomalies, integrated into Google Sheets for reconciliation. Saved an average of 40 hours per financing manager per month.

Customer support faced rising request volumes, with human agents spending too much time on resolvable cases and lacking seamless context when complex cases needed escalation.

Oversaw development of a multi-agent Retrieval-Augmented Generation chatbot handling Gozem support requests autonomously, reducing human agent workload while ensuring seamless escalation to Zendesk for complex cases. Added automatic conversation summarization to preserve context for human handoff.

Transportation operations had no live visibility on supply-demand imbalances during high-demand events (public holidays, major urban events), leading to slow operational response.

Architected a minute-granularity pipeline aggregating GPS, booking, and driver-availability signals. Built supply-demand imbalance detection with threshold-based alerts, plus an operational dashboard surfacing demand-density maps, supply-gap indicators, driver engagement scores, and event KPIs. Implemented automated Google Chat alerts and validated during the Vodun Days festival peak: 10.2% improvement in supply rate, 7.4% increase in request-to-completion rate, and 5.4% coverage gain across ~2,000 distinct users.