01
AI Strategy & Roadmap
Know exactly where AI creates value — and in what order to pursue it.
I translate executive strategy into a pragmatic, sequenced roadmap: high-value use cases,
build-vs-buy decisions, risk tiers, target architecture, and a governance operating model —
so the investment compounds instead of scattering across disconnected pilots.
- AI opportunity assessment
- Use-case prioritization & ROI modeling
- Reference architecture
- Build-vs-buy & model selection
- Responsible-AI operating model
- Adoption & change roadmap
02
Agentic & RAG Platform Engineering
Move from “interesting demo” to a platform that survives real users and real data.
I design and build production-grade multi-agent and retrieval-augmented (RAG) systems —
with the orchestration layer that unifies retrieval, agent routing, and tool use across
customer and internal experiences, in multi-tenant environments where isolation is mandatory.
- Multi-agent orchestration & routing
- RAG pipelines & vector search
- Tool-use & function calling
- Multi-tenant, multi-portal architecture
- Event-driven integration
- Evaluation & observability for AI
03
AI Governance, Security & Trust
Ship AI you can defend to your board, your auditors, and your customers.
I treat AI execution as its own security domain — governing what agents can retrieve,
reason over, combine, and act on. Defense-in-depth tenant isolation across identity, API,
and data layers; deterministic validation that routes AI output through format, source, and
business-rule checks before any write to a system of record; and an immutable audit trail.
- Defense-in-depth tenant isolation
- Responsible-AI guardrails
- AI data-integrity & trust governance
- Human-in-the-loop & risk tiering
- Prompt-injection & abuse controls
- Audit, provenance & compliance readiness
04
AI-Augmented SDLC & Modernization
Make your engineering org faster with AI — and modernize the estate AI runs on.
I bring GenAI into the software lifecycle (AI-assisted development, quality gates, faster
reviews, fewer post-release defects) and modernize legacy systems into cloud-native,
AI-native platforms with the integration fabric AI/ML workflows plug into.
- AI-assisted development & DevSecOps
- Quality gates & test-coverage lift
- Legacy-to-cloud-native modernization
- Microservices & integration fabric
- Observability, resiliency & SRE
- Platform cost & reliability optimization
05
Enterprise Applications & Integration
Connect the systems of record and systems of engagement your business actually runs on.
I've spent 25+ years architecting enterprise applications and the integration layer that connects
them — from Enterprise Enabler, a commercial EAI/ETL platform I architected at Stone Bond
Technologies (U.S. Patent: Integration Integrity Manager) adopted by Fortune 500 clients, to
a commercial-grade Enterprise Service Bus I later built that replaced legacy middleware and now
serves as the fabric AI/ML workflows plug into. I design the application, data, and integration
architecture behind ERP, CRM, and partner-facing systems, and lead the engineering teams that
build and run them.
- Enterprise application architecture
- ESB & EAI/ETL architecture
- API-led & event-driven integration (Kafka)
- B2B integration (RosettaNet, AS2, PIDX)
- Master & transactional data integration
- Legacy middleware modernization