Building the Future of
Autonomous Operations

Llewellyn Christian didn't learn procurement from a textbook. He learned it managing $100M+ in spend across Google's global cloud and data center operations, building asset lifecycle programs inside Apple's data centers in Cupertino, and redesigning IT procurement automation at Roblox. Before that, he built a shared procurement operating model from scratch at the Federal Home Loan Bank of San Francisco — rolling out Coupa P2P to 95% supplier adoption and establishing the contract governance and audit-ready processes that a regulated financial institution demands.

Over 20+ years at Meta, Google, Apple, Roblox, and Hayden AI, Llewellyn ran the programs that most enterprise software companies only demo. Vendor scorecards. SLA compliance frameworks. AI-driven lifecycle analytics. Cross-functional alignment across engineering, finance, supply chain, and compliance — not in a pitch deck, but in production, at hyperscale, with real dollars on the line. At Google alone, he directed 50+ global infrastructure and procurement programs delivering multi-million-dollar savings through vendor strategy and contract optimization.

That career became the blueprint for ODE. Every feature in the platform — three-way matching, multi-tier approval routing, role-based spend visibility, vendor lifecycle management — exists because Llewellyn spent two decades watching where enterprise procurement actually breaks. The gap between a purchase decision and its audit trail. The approval chain that exists in policy but not in practice. The invoice that sits in AP's backlog for 90 days because no one matched it to the PO and the receipt.

Llewellyn holds an MIT certification in AI Products & Services — earning an Exemplary distinction from MIT xPRO — and completed Stanford's Executive Program in Sustainability Leadership. He studied at the University of San Francisco (B.S., Information Technology & Management, Honors) and holds certificates in Procurement, Strategic Sourcing, and Executive Leadership from Cal State East Bay. He brings that academic rigor to ODE's AI architecture: an earned autonomy model where AI agents progress from assisted to autonomous only through demonstrated accuracy — because he spent a career watching automation fail when it skipped the trust step.