Systems architect & technical advisorAvailable for global engagements

Complex technology. Clear decisions. Dependable systems.

Independent architecture and hands-on delivery for leaders moving AI into production, modernizing AWS, or reducing legacy-system risk.

Request an architecture assessment Review production evidence

25+years in engineering

Japanindustrial R&D roots

2013AWS production since

R.E.E.licensed engineer

decision.system legible

EDGE DELIVERYCloudFront

INGRESSAPI Gateway

ORCHESTRATIONAWS Lambda

KNOWLEDGERAG / Vector

PERSISTENCES3 / SQL

pattern: event-drivenmode: reference

$ clarify --system enterprise-aidecision path ready

Ex-Sumitomo R&D · R.E.E. · AWS production since 2013PSIA · IIEE · Makati, PH

When to bring me in

The cost of a wrong technical decision is rising.

The best time to involve a senior architect is before complexity hardens into operating cost, delivery risk, or a failed transformation program.

AI pilots are not surviving contact with production.

The demo works, but data quality, security, evaluation, cost, or ownership remains unresolved.

Cloud decisions are accumulating cost and complexity.

The platform needs a clearer operating model before another service, vendor, or rewrite is added.

A legacy system is blocking valuable product change.

The business cannot pause for a clean-sheet rebuild, but incremental modernization needs a credible path.

Leadership needs an independent technical point of view.

The team needs senior judgment that can connect commercial priorities to architecture and implementation.

Best fitFounders · CEOs · CTOs · Product leaders · Operations leadersIndependent advice, then practical execution.

Ways to engage

Senior judgment, sized to the decision.

Start with the smallest engagement that can create clarity. Expand only when the problem and the value justify it.

Describe the current constraint

Fixed-scope diagnosis

Architecture Clarity Sprint

Turn an ambiguous system problem into a legible decision: current-state risks, target architecture, priorities, and a practical next-step plan.

Focused production engagement

AI System Production Pilot

Take one valuable knowledge or workflow use case beyond the prototype, with retrieval, evaluation, guardrails, observability, and human handoff designed in.

Modernization roadmap

Cloud & Legacy Modernization

Define an incremental path that improves reliability, delivery speed, and maintainability without placing business continuity at risk.

Ongoing senior guidance

Fractional Systems Architect

Add experienced architecture judgment to product and engineering leadership without hiring a full-time executive or another layer of management.

Production evidence

Built, shipped, and operated.

The work stays close to implementation. These live systems demonstrate product architecture, interface delivery, deployment, and ongoing technical care.

01 / working AI

live

AI-enabled solution portfolio

SpiceWorx Solutions Library

AI knowledge-assistant demonstrations built around operational workflows, structured retrieval, and useful human handoff—not a collection of disconnected chat interfaces.

Constraint: Turn domain knowledge and recurring workflows into useful AI assistance without treating a chat interface as the product.
Architecture decision: Use retrieval-first flows grounded in selected source material, with explicit workflow context and human handoff.
Operating result: A live, maintained solution library demonstrating knowledge assistants across real business scenarios.

Knowledge systemsEnterprise automationFull-stack delivery

Explore live demos spiceworx.com

02 / managed cloud

live

Managed cloud delivery

ServerlessHub

Managed AWS serverless delivery focused on edge performance, a smaller maintenance surface, and predictable operations for business websites and applications.

Constraint: Deliver fast business sites globally without maintaining a conventional, always-on web-server fleet.
Architecture decision: Use private static origins, CloudFront edge delivery, event-driven services, and repeatable AWS deployment.
Operating result: A live managed-delivery model with no permanent web server for static sites and a deliberately smaller patch surface.

AWS serverlessCloudFront / S3Technical care

Review infrastructure live

Inspectable architecture

The decisions behind the claims.

Sanitized counterparts to production work make architecture reasoning inspectable without exposing client systems.

github.com/ruelabion

ruelabion / micro-rag-concept01

Enterprise AI reference

Micro-RAG Knowledge Engine

A small retrieval pipeline that ingests documents, retrieves matching passages from pgvector, and returns answers with validated citations. It refuses when the documents do not contain the answer.

Next.jsNode.jspgvectorClaude API

Architecture decision

Ingestion, retrieval, and generation are separate stages behind small interfaces, so each can be tested alone and the embedding or model provider swapped without touching the others.

Try the browser demo Read the concept repository Request the code

ruelabion / zero-overhead-serverless02

AWS infrastructure reference

Zero-Idle Serverless Reference Architecture

Interactive reference documentation for a secure, globally distributed AWS footprint with static edge delivery and event-driven compute.

AWS CDKCloudFrontLambdaMermaid

Architecture decision

Static edge delivery and on-demand compute reduce idle application infrastructure without implying that the whole system is cost-free.

Explore the architecture View repository

ruelabion / self-service-news-publishing03

Client delivery case study

Self-Service News Publishing System

An anonymized publishing workflow that lets a nontechnical editor create, preview, publish, hide, and restore website news without access to deployment credentials.

Sveltia CMSPythonGitHub ActionsAWS

Architecture decision

Content authoring is isolated from privileged deployment. Trusted automation validates every change and keeps the last known-good site live when publishing fails.

View the delivery case study Private client implementation

Public proof includes two reference repositories and an anonymized delivery case study. Private implementation details remain protected; Micro-RAG code is available on request through the assessment form below.

Engineering provenance

Industrial roots. Modern systems. No hype.

A career across industrial control, the early commercial web, enterprise platforms, cloud operations, and applied AI provides context for today’s architecture decisions.

“The job is not to introduce more technology. It is to make the system easier to understand, safer to change, and more useful to the people operating it.

Nearly four years developing C/C++ control software for Sumitomo Heavy Industries in Japan formed the engineering baseline I bring to web, cloud, and AI systems today: explicit constraints, legible behavior, and dependable change.

1996—1999

Sumitomo Heavy Industries, Ltd.

R&D Systems Engineer · Hiratsuka, Japan

C/C++ control software for laser-welding research and industrial robotics.

2000—2001

Independent Web Programmer

Full-stack delivery

Early web applications, distributed systems, and rapid client delivery.

2001—present

SpiceWorx Consultancy Inc.

Co-founder & Technical Consultant

Enterprise web platforms, AI assistants, integration, and long-term technical operations.

2013—present

AWS production systems

Cloud & serverless architecture

Managed production workloads and progressively adopted serverless delivery patterns.

Start with the real constraint

Bring me the decision that needs clarity.

Share what exists today, what is getting in the way, and what the business needs next. I’ll respond with an initial technical perspective and a sensible next step.

No generic sales sequence or mailing list
Advice grounded in operating constraints
Advisory and hands-on delivery available

Prefer direct correspondence?ruelabion@gmail.com

project-context.req direct channel