Cloud & AI-native architecture
Secure, AWS-first foundations designed for agents and AI workloads from the start, not retrofitted onto infrastructure that was never meant for them.
AI-native software,
engineered to last.
We turn complex engineering into well-architected systems, built with craftsmanship & artistry.
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What we deliver.
Project contracts or fractional engineering leadership: from green-field AI platforms to untangling code that got away from you, across the whole lifecycle and held to a craftsman's standard.
Agentic systems & RAG
Production agents on Amazon Bedrock and AgentCore, with retrieval that stays grounded in your data and answers you can actually trust.
DevOps & delivery
CI/CD and infrastructure as code (CDK-first) that make deploys boring, with observability and reliability built in from day one.
Platform modernization
Turn aging systems into cloud-native, AI-ready platforms, incrementally and without betting the company on a big-bang rewrite.
Web & product engineering
Fast, accessible sites and applications: static-first where it fits, server-rendered where it doesn't, with performance and SEO built in.
AI code cleanup
Tame vibe-coded and AI-generated sprawl into systems your team can actually read, maintain, and extend.
For founders: fractional CTO & engineering leadership
Have a real product but no technical lead? We can run your engineering: architecture, the build, and the early hires, all without a full-time CTO on the cap table. From the first version to a system your team can own.
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What we've built.
Stealth Startup
in stealth
A complete enterprise platform we designed and built end to end for a highly regulated, high-stakes industry. One system runs the entire lifecycle: client acquisition (discoverability, intake, CRM, marketing automation) through complex, multi-stage case execution and resolution. A public-facing surface and the internal operating system share a single data layer, so a record's source and intake carry through to the final outcome with nothing re-keyed.
The hard part is governed AI. A fleet of domain-specialist agents orchestrated across multiple models on AWS Bedrock, each grounded in tenant-scoped retrieval, then gated, versioned, and audited so nothing reaches an end user without an explicit, human-approved state transition. Every run replays against the exact context it saw, and an organization's memory and approvals stay portable across model providers. AWS-native and serverless throughout, scaling from public consumer traffic down to confidential, permission-aware workloads. This is the governed, auditable multi-agent AI most of the field is still working out in theory.
<About />
Who you're working with.
For fifteen years I've designed, built, and scaled distributed systems (AI and ML platforms, cloud-native services, and observability at volume) across fintech, retail, enterprise infrastructure, and developer platforms. I've shipped LLM platforms used across product lines, Kubernetes-native MLOps, and telemetry pipelines that carry production traffic at scale.
My work blends deep engineering discipline with AI-native tooling. I architect resilient cloud infrastructure, stand up the ML and LLM systems that run on it, modernize platforms that have aged past their design, and stay hands-on in the code the whole way. Whether it's a green-field AI build or a system that's gotten away from a team, the goal is the same: software that's scalable, observable, and still maintainable years from now.
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