Product Builder · Architecture Advisor
AI-assisted products, built with architecture discipline.
I build consumer apps for personal records and receipt evidence. I also advise teams on AI, integration, cloud modernization, and delivery-risk decisions.
Two ways this work shows up
Build focused products. Advise on consequential systems.
I build focused AI-assisted products and advise teams on architecture decisions where reliability, integration, AI readiness, and delivery risk matter.
App Builder
Focused AI-assisted products for useful personal records.
Focused AI-assisted products for personal records, receipt evidence, semantic search, and practical reporting.
- ExpenseJournal in MVP/QA
- Receipt and document evidence workflows
- Personal health organizer direction
Architecture Advisory
Concrete architecture review for delivery risk.
Concrete architecture review for AI readiness, integration boundaries, cloud modernization, rollback, observability, and ownership.
- AI production readiness
- Integration and cloud modernization
- Decision memo, risk register, recommended path
Domain depth
Domain depth behind the advisory work.
Most architecture problems are not abstract. They show up in banking onboarding, payment flows, healthcare interoperability, insurance integrations, and legacy-to-cloud modernization.
Banking transformation
Banking systems with real operating pressure.
Experience across core banking transformation, digital banking onboarding, retail and business banking flows, commercial lending systems, business banking payments, and credit-union platform integration.
Integration modernization
From integration-developer roots to cloud boundaries.
From BizTalk and ESB modernization through Azure Logic Apps, API Management, event-driven architecture, Service Bus, reconciliation, retries, and cloud workflow platforms.
Healthcare and insurance
Interoperability where quality and ownership matter.
Healthcare integration and life insurance integration experience where HL7, FHIR, interoperability, data quality, workflow reliability, and operating ownership matter.
Cloud and AI production
Production AI depends on platform discipline.
Multi-cloud architecture across AWS, Azure, and Google Cloud with Kubernetes, serverless, AI production readiness, RAG, semantic search, observability, and human review.
Selected Insights
Three current notes worth starting with.
What a senior architect should force early in a cloud modernization program
How to make sequencing, ownership, and delivery risk visible before the roadmap gets expensive.
How integration architecture decisions quietly determine delivery speed
Why boundaries, contracts, retries, and reconciliation paths shape delivery more than tooling alone.
Where enterprise AI programs fail first: system boundaries, retrieval design, and operational ownership
The architecture questions that decide whether an AI workflow survives production behavior.
Next step
Choose the conversation that matches your intent.
Share product feedback on ExpenseJournal or book a focused architecture advisory conversation.