From Pilot to Production: AI Engineering for FinTech

Most AI initiatives don't fail during the pilot. They fail after the pilot.
The demo works. Stakeholders are impressed. The business approves the next phase. Then reality arrives: messy data, changing workflows, compliance requirements, audit requests, model drift, unexpected costs, and systems that become impossible to explain or maintain.
The challenge is building AI systems that continue working under real operational conditions.
This interactive 60-minute workshop is designed for FinTech founders, engineering leaders, and operations teams who are moving beyond experimentation and into production.
We'll work through practical exercises using your own business processes. You'll identify a real decision that could be automated, evaluate whether it's actually ready for automation, define authority boundaries between AI and humans, and uncover the hidden risks that cause production deployments to fail.
During the session, you'll learn:
• Why successful pilots often fail to reach production
• How to identify the right process to automate first
• The three levels of AI adoption: Assistance, Automation, and Coordinated Systems
• How to define what AI can do, what requires human review, and what must never be automated
• The six architectural layers required for production AI systems: Signal, Thinking, Rules, Execution, Audit, and Monitoring
• Common failure patterns including workflow debt, model drift, latency chains, and governance gaps