A curated bench of vetted AI workforce specialists.

Ph.D. in Strategic Management (University of Maryland) with a career spanning executive advisory, financial governance, and AI workforce strategy. A Fellow of the ACCA and Certified Professional Accountant (CPA, Canada), Wunmi helps organizations make AI workforce decisions that hold up to board and regulatory scrutiny.

MSc Computer Science (Data Science), Dalhousie University. Certified across Microsoft Azure, Databricks, and AWS, Shile leads the technical delivery of data foundations and AI engineering capability, ensuring the infrastructure behind AI initiatives is production-ready, governed, and built to scale.

Designs enterprise-scale AI solution architectures that integrate cleanly with legacy core systems, with particular depth in regulated and safety-critical environments.

Master of Entrepreneurship in Technology Innovation Management (Carleton University). A Project Management Professional (PMP) and Certified Scrum Master (CSM), Toye leads programme delivery across AI and workforce transformation engagements, combining entrepreneurial thinking with disciplined execution.

Builds AI governance frameworks that practitioners actually use, tiered risk review, model documentation standards, and regulator-ready audit trails.

Leads end-to-end delivery for AI accelerators and prototypes, balancing speed-to-value with the governance discipline needed for a credible scale decision.

Builds and validates the models behind AI products, with particular strength in evaluation rigor for high-stakes use cases where being wrong is expensive.

MSc Data Engineering from Edinburgh Napier University, Scotland, with a full stack of Microsoft Azure, Databricks, and IBM Data Science certifications. Temi builds the reliable, governed data foundations that AI initiatives depend on to reach production.

Assesses AI systems for security, privacy, and operational risk before they reach production, with a focus on practical controls that delivery teams can actually implement.