Strategy, architecture, and hands-on delivery—from someone who has built agentic AI products, not just advised on them.
Most AI advice comes from people who have read about it. My experience is different: I led product strategy for agentic AI at Digibee, a leading integration platform, where I defined and shipped AI features for enterprise customers—including agentic orchestration, AI-assisted development tooling, and AI-native integration patterns.
Senior Director of Product at Digibee — Led agentic AI product strategy and delivery, AI-assisted development tooling, and AI-native integration patterns for enterprise customers.
I've built enterprise-ready AI products that handle real-world complexity—agentic workflows, governance frameworks, production deployment. That's implementation experience, not just advisory work.
Opportunity identification, readiness gaps, prioritized roadmap, and board-ready narrative. The starting point for most AI engagements.
Learn more →Hands-on AI PoC delivery. Build the technical proof point before committing to a full build. Especially valuable for agentic AI use cases.
Learn more →Your AI strategy is only as good as your integration architecture. Design for agent connectivity, data accessibility, and AI-era governance.
Learn more →Turn AI feature ideas into implementation-ready plans. Validate the customer problem, assess AI technology options, define the solution—before committing engineering resources.
Learn more →Embedded part-time technology or product leadership for sustained AI execution, architecture guidance, and strategic direction.
Learn more →Ad-hoc or retainer access for AI strategy decisions, vendor evaluation, and gut-checks when you need a senior perspective fast.
Learn more →Sustained leadership for ongoing execution and strategic guidance.
Fractional Leadership →On-demand access for validation, coaching, and strategic gut-checks.
Advisory Retainer →