Case Studies
Detailed breakdowns of how I approach architecture, modernization, cloud delivery, data modeling, secure integrations, and AI-assisted development.
Secure payments
Modernizing a Secure Online Payment Workflow
An anonymized AWS-hosted pattern for API-first payment workflows where reliability, auditability, and compliance-minded delivery matter.
Problem
Payment workflows need to be reliable, traceable, secure, and easy to upgrade without interrupting business operations.
API Design
Keep integration boundaries explicit with predictable request/response contracts, validation, logging, and failure handling.
AWS Implementation
Run the platform with production-oriented AWS deployment practices, controlled releases, operational monitoring, and database-backed transaction workflows.
Security Controls
Use encryption-aware design, access controls, audit logging, and release discipline aligned with PCI-style expectations.
Operational Reliability
Plan upgrades, regression checks, and production support so annual compliance or partner changes do not become emergency rewrites. This mirrors real payment-platform upgrade work that consistently passed stringent third-party security testing.
Modernization
Delphi Legacy Modernization Strategy
A step-by-step strategy for improving Delphi, WinForms, Access, or older desktop systems without a risky big-bang rewrite.
Current-State Analysis
Inventory modules, forms, data access patterns, integrations, deployment process, and business-critical workflows.
Business Logic Documentation
Capture rules from code, stored procedures, user behavior, and operational knowledge before changing boundaries.
Database Review
Identify schema risks, legacy Access or SQL Server dependencies, migration scripts, reporting queries, and data integrity checkpoints.
Migration Path
Choose refactor, wrap, replace, or rebuild per module based on value, risk, maintainability, integration complexity, and user disruption. The goal is practical continuity: phased modernization, zero-downtime cutover planning where possible, and data integrity checks during migration.
Blazor
Blazor Dashboard & CMS Architecture
A maintainable architecture for database-driven dashboards, multilingual commerce/CMS screens, reporting modules, and internal business tools.
Component Structure
Build reusable tables, filters, forms, summary cards, and workflow panels with clear ownership and predictable state.
Data Flow
Keep data access behind services, use view models intentionally, and avoid leaking database concerns into UI components.
Cloud Delivery
Deploy business platforms such as multilingual e-commerce and AI-backed restaurant operations systems on AWS with database-backed workflows, data import from mainstream platforms, and release coordination.
Delivery Outcomes
Use measured release planning and scope control. Comparable delivery work included multilingual systems shipped on time and roughly 20% under budget.
Performance
Use pagination, projection queries, loading states, caching where appropriate, and careful rendering for high-density dashboards and reporting-heavy screens.
Restaurant operations
AI-Backed Restaurant Operations Platform
A production AWS-hosted platform where server-side AI powers daily restaurant workflows and imports whole datasets from mainstream platforms so owners do not start from scratch.
Problem
Restaurant teams need unified ordering, inventory, reservation, and management tools, but replacing an existing POS or operations system usually means manually rebuilding menus, stock, schedules, and history.
AI-Backed Server
The platform is built on a fully AI-backed server layer that supports operational logic, data normalization, and intelligent handling beyond static CRUD workflows.
Platform Import
Whole restaurant datasets can be imported from mainstream platforms—menus, inventory, reservations, and related operational data—using AI-backed server logic to map and validate incoming records.
Onboarding Without Scratch
Migration procedures run through the platform itself, so restaurants already using other systems can transition without re-entering everything manually.
Multi-Surface Delivery
Operational workflows ship across desktop, web, and mobile on AWS with database-backed consistency, testing support, and practical day-to-day user flows.
AI development
Using AI Agents to Move From Idea to Product
A practical approach to using AI agents as engineering acceleration while keeping architecture, prompts, acceptance criteria, and review under human control.
Architecture First
Break the product into components, workflows, data models, prompts, service boundaries, and acceptance criteria before asking agents to implement.
Azure + OpenAI API
Use Azure for the AI Job Matching Platform and OpenAI API-backed backend logic for job description analysis, resume analysis, match scoring, and explainable output.
One-Week Build
The AI Job Matching Platform reached a production-ready prototype in one week because the work was planned as small agent-ready tasks with detailed prompts and review checkpoints.
Agentic Delivery
Use Copilot, Cursor, Claude, Gemini CLI, Antigravity-style workflows, generated tests, debugging support, and documentation prompts while preserving human product judgment.