What I build for clients.
Three practices, one discipline: measure it, then ship it. You engage one senior architect — AI-accelerated and held to enterprise gates — across data, AI, and product. No agency layers, no overhead: enterprise-grade capability, without the enterprise price tag.
Converged-database architecture & performance
Most teams stitch together a handful of specialized datastores and a web of sync pipelines. I design on a converged engine instead — one source of truth, fewer moving parts, and measurably faster at the workloads that matter. Thirty-plus years and a reproducible benchmark program stand behind every recommendation.
When a migration is unavoidable, I move workloads across engines without rewriting application logic. Proof: matched-compute benchmarks (17× graph traversal, 6.2× schema validation) and a 205-test translation engine — see the Work →
- Converged-database architecture & data modeling (Unified Model Theory)
- Performance engineering — schema validation, aggregation, binary-format access
- Cross-engine migration without application rewrites
- Document, graph, time-series & relational as one canonical form
Agents, retrieval, and defensible automation
I build AI that's safe to put in front of real work: agent infrastructure that remembers across sessions, retrieval grounded in your own data, and automation with a hard determinism boundary — the model writes the prose, never the authoritative numbers.
It's also how I deliver — AI as a governed pair-programmer under strict gates, which is what makes enterprise-grade output affordable. Proof: production agent infrastructure, an enterprise RAG reference, and fail-closed document automation — see the Work →
- Agentic infrastructure & context persistence (MCP)
- Enterprise retrieval-augmented generation (RAG)
- Defensible automation — deterministic engine, fail-closed anonymization
- AI-driven development, governed by TDD & security gates
Production systems, built and operated
I design, build, and operate complete production systems — not prototypes, not slide decks. Secure by default, highly available, fully tested, and held to a measured quality bar on every page before it ships.
And I run them: dual-AZ active-active in production, not a hand-off. Proof: a live, revenue-earning SaaS at 99/98 Lighthouse with 8-layer security and a 2:1 test-to-code ratio — see the Work →
- Full-stack production SaaS, end to end
- Defense-in-depth security — 8 independently testable layers
- Dual-AZ high availability — built and operated, not handed off
- Lighthouse-100 quality bar & strict TDD as release gates