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aceymagallanes/README.md

Automate the routine. Escalate the exception.

I'm Acey Magallanes. I spent 15+ years leading business transformation and program delivery at HP, Orica, and Singtel. Then I stopped writing recommendations about automation and started building it.

Everything below is working software: real workflows, documented architecture, governance models, and ROI math. All demos run on synthetic data.

n8n Python TypeScript Claude API Power BI Lean Six Sigma GitHub Pages

The systems

System The routine it automates The exception it escalates
Circular ESG OS Tracking end-of-life device recovery and consolidating ESG disclosure data Recovery shortfalls and compliance risks, surfaced through a streaming Claude Copilot
Atlas PMO Command Center Consolidating status, milestones, and risks across a multi-project portfolio Projects drifting on schedule, budget, or risk, escalated to program leads
Velocity Engine Reading, scoring (BANT), and routing every inbound lead High-value leads flagged for immediate human follow-up
SupportOps AI Ticket triage and SOP matching for support teams Cases with no matching SOP, routed to specialists
Contract Review Tool Clause extraction and first-pass contract risk scanning High-risk language sent to a legal reviewer with full context
AP Control Tower Validating and matching supplier invoices Fraud signals investigated by an agentic AI advisor, then a human
AI Logistics Command Center Monitoring warehouse routing, courier risk, and inventory exposure Revenue-at-risk alerts surfaced to operators before they become losses
Incident Intelligence Classifying and prioritizing incoming IT incidents Unusual failure patterns and root-cause anomalies, routed to engineers

Live dashboards are linked inside each repository.

Where this comes from

15+ years of transformation and program delivery at HP, Orica, Singtel, and NCO Group across Asia Pacific, the US, and Europe. Lean Six Sigma Black Belt, ITIL, COPC. The numbers behind the discipline: US$335K in annual automation savings, process cycle times cut 30%, and 1M+ product units through closed-loop operations.

How every build works

  1. Discovery with the people who actually do the work
  2. Process redesign with Black Belt discipline, before any tool is chosen
  3. Build in n8n, Python, or TypeScript and React, with LLM APIs for reasoning
  4. Governance model and ROI case signed off before go-live

People keep the judgment calls. Software takes the repetition.

Find me

Portfolio: https://aceliora.com LinkedIn: https://www.linkedin.com/in/aceymagallanes Email: aceymagallanes624@gmail.com

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  1. atlas-pmo-command-center atlas-pmo-command-center Public

    AI-powered multi-project PMO command center — Next.js, TypeScript, Tailwind. Live demo via GitHub Pages.

    TypeScript

  2. circular-esg-os circular-esg-os Public

    An AI-powered Circular Economy Operating System: ESG control tower for enterprise end-of-life device recovery, with a streaming Claude Copilot.

    TypeScript

  3. incident-intelligence incident-intelligence Public

    AI-powered IT incident triage built with n8n, the Claude API, and a live dashboard

    HTML

  4. supportops-ai supportops-ai Public

    Customer support intelligence workspace for AI triage, SOP matching, workflow automation, and support operations insights

    JavaScript

  5. velocity-engine velocity-engine Public

    AI engine that scores and routes inbound leads in real time — reads each lead's message, scores it on BANT with Claude, and cuts first response from ~42 hours to minutes. Includes an interactive ex…

    Python

  6. ai-logistics-command-center ai-logistics-command-center Public

    Executive-grade AI logistics control tower for warehouse routing, courier risk, inventory exposure, exception management, and revenue-at-risk insights

    Python