530
repositories mapped within a healthcare SaaS estate
Michael Andrew Hood — Principal Software Architect
Enterprise architecture for systems that have to scale.
I help SaaS organizations understand complex application estates, modernize .NET platforms, standardize client integrations, and prepare engineering workflows for AI-enabled delivery.
Enterprise architecture, modernization strategy, production engineering, and platform governance across healthcare SaaS, travel, logistics, retail, security, payments, and cloud environments.
Outcomes
Architecture outcomes that change delivery
High-signal results from enterprise estate work, client integration productization, and deployment transformation. Figures are provided for verification before publication.
83
APIs and approximately 2,000 endpoints assessed
11
customer-facing applications represented
72
healthcare client integration contexts supported
1 week → hours
client architecture preparation reduced from approximately one week to hours
2 weeks → 1 day
role-focused onboarding reduced from approximately two weeks to one day
annual → ~4 hours
architecture refresh cycles reduced from annual manual work to approximately four hours
months → ~1 hour
retail software installation reduced from several months to approximately one hour
The healthcare SaaS estate spans 530 repositories, including approximately 500 component repositories, 40 priority services, 83 APIs, approximately 2,000 endpoints, and 11 customer-facing applications.
Architecture statement
Architecture is useful only when it changes decisions.
I use architecture models, reference patterns, implementation standards, and code-level understanding to help organizations sequence modernization, reduce implementation risk, improve engineering adoption, and scale product delivery.
Architecture documentation is not the end product. It is a mechanism for creating shared understanding, exposing dependencies, evaluating tradeoffs, accelerating onboarding, standardizing integrations, and aligning technical change with business direction.
Capabilities
Where I create leverage
Enterprise visibility, SaaS integration productization, .NET/cloud modernization, AI-enabled SDLC foundations, and production-grounded systems work.
Enterprise architecture and estate visibility
- Estate-wide architecture modeling
- Product and platform boundary definition
- Application portfolio assessment
- Dependency and integration mapping
- Architecture governance
- Technical risk identification
- Modernization sequencing
SaaS and client integration architecture
- Client integration reference architectures
- Reusable implementation patterns
- Component, sequence, flow, and data-movement diagrams
- Data-transfer agreement documentation
- Productization of client delivery
- Integration repeatability
- Customization-boundary strategy
.NET and cloud modernization
- Legacy .NET estate assessment
- Modern .NET migration strategy
- Monolith decomposition
- Strangler-pattern modernization
- Service-layer extraction
- API modernization
- Azure architecture
- CI/CD and delivery modernization
AI-enabled SDLC and architecture automation
- Repository and context ingestion
- Codebase analysis
- Architecture assessment automation
- Code-derived architecture documentation
- Jira and Confluence ingestion
- Human-reviewed architecture generation
- Developer workflow modernization
- AI modernization readiness
Production systems and integration
- Transactional commerce workflows
- Payments, refunds, and cancellation systems
- Event-driven integration
- MuleSoft integrations
- Azure Event Hub
- SQL Server transactional systems
- Production troubleshooting
- Reliability and data consistency
Work
Selected architecture case studies
Public-safe stories about estate visibility, client integration productization, AI-ready context, production commerce, and deployment transformation.
Challenge
System knowledge was distributed across code, documents, teams, Jira, Confluence, diagrams, and tribal knowledge. Leadership and engineering needed a consistent way to understand product boundaries, integration dependencies, modernization risk, and delivery impact.
Approach
- Created estate-wide architecture views.
- Created per-product views.
- Mapped integrations and data movement.
- Created workflow-level views for critical processes.
- Connected higher-level architecture to code and repository context.
- Created views appropriate for executives, product teams, architects, engineers, and onboarding.
- Used architecture artifacts as inputs to modernization sequencing and risk assessment.
Decisions & tradeoffs
The result was not merely better documentation. It was an architectural operating model that enabled more consistent modernization, delivery, onboarding, and product decisions.
Results
- Established a shared model of the application estate.
- Improved role-focused onboarding from approximately two weeks to one day.
- Reduced architecture and high-level-design refresh cycles from annual manual work to approximately four hours.
- Supported modernization planning across the full estate.
- Improved visibility into product boundaries, integrations, dependencies, and client-delivery concerns.
- Influenced architecture and modernization practices across 15 teams.
Challenge
Client-facing teams, product, architects, engineering, and implementation stakeholders needed a reusable language for discussing systems, workflows, data movement, dependencies, and delivery risks.
Approach
- Developed reusable component diagrams.
- Developed sequence diagrams.
- Developed flow diagrams.
- Created workflow models.
- Created data-transfer agreement documentation.
- Distinguished product capabilities from client-specific configuration.
- Moved architecture earlier into product and client conversations.
- Established patterns that could be reused and adapted rather than recreated.
Decisions & tradeoffs
Productization of integration patterns is as important as individual solution quality. Clear customization boundaries reduce long-term estate complexity.
Results
- Reduced client architecture preparation from approximately one week to hours.
- Improved consistency across client discussions.
- Made integration assumptions and data movement visible earlier.
- Reduced downstream ambiguity and implementation risk.
- Supported the transition from custom client delivery toward repeatable SaaS implementation models.
More case studies
AI-ready context ingestion
Created the initial context-ingestion architecture and repository automation needed for future AI-assisted analysis — foundation, not autonomous platform.
~500 component repositories in scopeCode-derived architecture
Designed an approach that derives structural architecture facts from code while routing intent and correctness through architect review.
Architecture refresh: annual → ~4 hoursCommerce platform modernization
Hands-on work across APIs, payments, refunds, cancellations, integrations, and modernization — architecture grounded in production consequences.
Retail deployment transformation
Led architecture and automation that reduced retail storefront installation from several months to approximately one hour.
Installation: months → ~1 hourExperience
Selected experience
An executive timeline of architecture leadership and hands-on modernization — not a full résumé dump.
Software Architect, Enterprise Architecture & AI Modernization — Healthcare SaaS Company
Leading enterprise architecture, client integration standardization, .NET estate modernization, architecture automation, developer-experience improvement, and AI-enabled SDLC readiness for a post-acquisition healthcare SaaS company.
- 530 repositories
- 40 priority services
- 83 APIs
- approximately 2,000 endpoints
- 11 customer-facing applications
- 72 client contexts
- 15 teams influenced
Application Architect / Senior Software Engineer, Client Engagements — TEKsystems
Client engagements spanning enterprise commerce, payments, integrations, API modernization, and distributed .NET platform modernization.
Vail Resorts
Enterprise commerce, payment, integration, API modernization, and production systems across guest reservations, refunds, cancellations, rentals, lift access, lessons, scanning, and food-and-beverage workflows.
Werner Enterprises
Application architecture and platform modernization across mobile, web, internal platforms, external applications, .NET APIs, monolith decomposition, Azure, and CI/CD.
Application Architect, Azure Cloud Microservices, Product Owner & Team Manager — IBM
Led client-facing architecture and delivery across three teams for retail point-of-sale, tax and accounting applications, internal tools, storefront installations, hybrid cloud, and back-office systems.
Key outcome: Reduced retail storefront installation time from several months to approximately one hour.
Associate Software Developer — AppRiver
Built and supported SaaS applications, internal tooling, Windows applications, eventing systems, installers, drivers, and cloud services serving 60,000 companies and 10,000,000 mailboxes.
Key outcome: Led a critical SecureSurf Desktop Agent initiative that prevented a major outage and preserved use across approximately 1,500 companies.
Approach
How I approach architecture
Principles that keep architecture connected to decisions, delivery, product boundaries, and code.
Architecture is a decision system
The purpose of architecture is not to produce diagrams. It is to improve the quality, speed, and consistency of decisions across product, engineering, implementation, and leadership.
Modernization is sequencing, not rewriting
Large estates cannot be modernized responsibly through indiscriminate replacement. Modernization requires dependency awareness, risk prioritization, incremental boundaries, and a credible transition architecture.
Product boundaries are part of the architecture
When a SaaS company accepts unlimited client-specific behavior, technical complexity becomes a business-model problem. Architecture should help define what belongs in the product, what belongs in configuration, and what should not be supported.
Architecture should remain connected to code
Static documentation becomes stale. Architecture should increasingly be derived from repositories, interfaces, deployment metadata, and runtime evidence, while preserving human review of intent and correctness.
AI requires context and governance
AI-assisted modernization depends on accessible organizational context, evaluation, traceability, human approval, and clear boundaries. Context ingestion is an architecture capability, not merely a prompt-engineering task.
Principal architects stay close to delivery
Architecture judgment improves when it remains grounded in APIs, data movement, production constraints, deployment systems, integration behavior, and the consequences of implementation decisions.
Contact
Let’s talk about the systems behind the roadmap.
I am interested in conversations about enterprise architecture, SaaS modernization, .NET platform strategy, client integration architecture, developer experience, and AI-enabled engineering transformation.