Bryan M.

I help founders and operators turn messy operations data into automation that pays for itself: AI workflows, dashboards people trust, and MVPs that ship. My platform Artemis processes ~10,000 orders a day and cut one client's return rate from 24% to 18% in a month. I start by asking what the problem costs you now, then build only what moves that number. Sometimes the answer isn't software, and I'll tell you that too. WHAT THAT LOOKS LIKE IN PRACTICE Artemis (founder & lead engineer): an analytics and automation platform for cash-on-delivery e-commerce. Return-to-sender is the biggest cost line in that business and almost nobody measures it properly. I built reporting that breaks RTS down by product, confirming agent, rider, province, price band and customer order history, then the automation that acts on it: SMS, chat and AI voice-call confirmations, and a risk-classification rule set that decides which orders are worth confirming at all. For one client that took returns from 24% to 18% within a month. The data behind it comes from n8n and Puppeteer pipelines pulling daily sales, inventory and purchase orders out of an ERP with no usable API: authenticated sessions, 350,000-row tables, browser sessions dropping mid-run, until I rebuilt the extraction to call the underlying data endpoint directly. Automation that survives production is a different job from automation that demos well. I also build the full-stack web apps behind it: Laravel, Next.js and Vue front to back, from admin dashboards and client portals to customer-facing apps. Other work: • BetterSeller: technical lead on an Amazon seller analytics platform (SP API, Advertising API, Gmail integrations) • Stallion Express: delivery management system for Canadian online sellers • BeApplying: lead engineer; AI-generated job descriptions and meaning-based candidate matching • Rush (white-label e-commerce), Globe Rewards (telecom rewards backend) HOW I WORK WITH YOU 1. AI Automation & Data Sprint (2–4 weeks, fixed price). We pick one costly process or untrusted dataset, I audit it, build the pipeline, automation or dashboard, and hand it over documented. 2. Care Plan (monthly). Monitoring, fixes and iterative improvements so the system keeps paying off after launch. 3. AI-powered MVPs and web apps for founders. Scoped, milestone-based builds from spec to production. STACK AI & automation: OpenAI/LLM APIs, n8n, webhooks, Puppeteer, AI voice (ElevenLabs, Twilio) Data: PostgreSQL, MySQL, ETL pipelines, reporting and dashboards, reconciling numbers across systems Apps: TypeScript, React, Next.js, React Native, Vue/Nuxt, Node/Express, Laravel/PHP, Python Infra: AWS, Docker Eight years of product engineering. BS Computer Engineering, Batangas State University. Based in Manila, working comfortably with US, EU and Australian hours. Tell me what's slow, manual or breaking, and what it's costing you. I'll tell you honestly whether I'm the right person for it, and what I'd build first.