I work at the intersection of Chemical Quality (QA/QC), data analytics, automation, and web development.
My focus: build systems that help teams capture quality data correctly, find it fast, and use it to improve decisions.

• Chemical QA/QC: finished products, physicochemical parameters, traceability & documentation
• Web systems: frontend + backend + databases for internal tools
• Data & automation: workflows and interfaces that reduce friction and improve data quality

• Languages: TypeScript, JavaScript, Python
• Web: Next.js (App Router), Tailwind CSS, Supabase
• Database: PostgreSQL (PLpgSQL), SQL
• Automation: n8n, GitHub Actions
• Other: VPS, Git/GitHub, Docker, Power BI

Enterprise Quality Control Platform (QA/QC)
A robust system designed to modernize industrial production logging and quality assurance.

• Purpose: Centralize laboratory standards, real-time production monitoring, and Non-Conforming Reports (NCR) management.
• Tech Stack: Next.js (App Router), TypeScript, Tailwind CSS, Supabase, TanStack Table, Zod, and shadcn/ui.
• Key Features:
  • Live Production Log: High-precision data capture for real-time monitoring.
  • Advanced Analytics: KPI dashboards (e.g., pH conformity) and automated PDF/Excel reports.
  • Role-Based Security: RBAC implementation for laboratory, production, and admin roles.

Logistics & Procurement Tracking System
Specialized internal tool for "Cloro de Hidalgo" to optimize raw material supply chains.

• Purpose: Automate the lifecycle of purchase requisitions and coordinate delivery logistics.
• Tech Stack: Next.js, TypeScript, Supabase (PLpgSQL), and Tailwind CSS.
• Key Features:
  • Procurement Calendar: Visual tracking of technical and logistics delivery schedules.
  • Multi-Role Approval: Integrated flow between Laboratory and CEDIS to ensure supply integrity.
  • Real-time Status: End-to-end monitoring from "Pending" to "Delivered" with instant updates.

• Improved UI and streamlined information processing for production/quality logging
• Reduced time and friction in data capture and record-keeping

Open to: opportunities, code reviews, ideas, contributions, and suggestions.

Google Antigravity · Stitch · Google AI Studio · NotebookLM · Claude Code · Git/GitHub

• Good manufacturing practices mindset: traceability, standardization, clear documentation
• Data quality first: validation, constraints, consistent identifiers, audit-ready logs
• Security by default: least privilege, secrets management, safe deployment habits
• Pragmatism: build small, measurable improvements that stick

Spanish (native) · English

Portfolio link: (coming soon)