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Kyle Andrew Dumipnas

AI Automation Engineer & SaaS Developer

I design and build n8n and GoHighLevel automations, and the backend services that run behind them: Python, FastAPI, and Node.js. Modular demos, built with the same concepts and technologies used in production, demoed on video.

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Or find me on GitHub · Résumé

automation.flow
GHL New lead contact created n8n Webhook trigger receives the payload n8n Filter intent = support n8n Score priority = high GHL Update contact ✓ synced to CRM

Built with

Python
FastAPI
Node.js
n8n
GoHighLevel
Docker
GitHub
Supabase
PostgreSQL

Selected work

Modular demos: 4 automations in n8n and GoHighLevel, built with the same concepts and technologies used in production.

AI Lead Qualifier

New GoHighLevel leads are automatically scored and qualified by AI before they reach a human, so only real opportunities get a follow-up call.

Client
—
Timeline
—
Complexity
Medium
Impact
Only qualified opportunities reach a human for a follow-up call.

Workflow steps

  1. 1 New lead is created in GoHighLevel.
  2. 2 Lead details are scored by an AI model.
  3. 3 Qualified leads are flagged for follow-up.
  4. 4 Unqualified leads are routed to nurture instead of a call.

AI-Powered Email Triage

Incoming emails are auto-classified by intent, then forwarded, auto-replied to, or dropped based on category, with no manual sorting.

Client
—
Timeline
—
Complexity
Medium
Impact
Response time on urgent emails drops from 'whenever someone checks the inbox' to under a minute, support senders get an instant acknowledgment instead of silence, and spam never reaches a human.

Workflow steps

  1. 1 Gmail trigger polls the inbox every minute — nothing gets missed.
  2. 2 Each email is classified by AI as SALES, SUPPORT, SPAM, or URGENT.
  3. 3 A Switch node acts on the category: SALES and URGENT are forwarded immediately, SUPPORT gets an instant auto-reply, SPAM is silently dropped.

Demo video coming soon

Workflow Version Control to GitHub

n8n workflows are auto-synced to a GitHub repo on every change, giving every automation a real version history and a rollback path.

Client
—
Timeline
—
Complexity
Medium
Impact
Every workflow change is versioned and reviewable, with a real rollback path instead of relying on n8n's built-in history.

Workflow steps

  1. 1 n8n workflow is saved or updated.
  2. 2 Change is detected and exported as JSON.
  3. 3 Export is committed to a GitHub repo.
  4. 4 Full version history and diffs become available in Git.

Demo video coming soon

File Ingestion + RAG + Auto CRM

Incoming documents are parsed and processed with a retrieval-augmented AI pipeline, then used to auto-populate CRM records, eliminating manual data entry.

Client
—
Timeline
—
Complexity
High
Impact
Eliminates manual data entry from incoming documents into the CRM.

Workflow steps

  1. 1 Document arrives (upload or inbox trigger).
  2. 2 Text is parsed and chunked for retrieval.
  3. 3 Retrieval-augmented model extracts the relevant fields.
  4. 4 Extracted fields auto-populate the CRM record.

How an automation gets built

Same process on every project, whether it's n8n or GoHighLevel underneath.

build.log

  1. map-workflow

    Walk the manual process end to end: the tools, the handoffs, the steps someone repeats every day.

  2. build-automation

    Triggers, logic, and error handling in n8n or GoHighLevel, version-controlled and not a black box.

  3. ship-and-handoff

    Runs in production, documented, with a clear owner for changes after I'm gone.

About

whoami
Kyle Andrew Dumipnas

I build automation systems on n8n and GoHighLevel, the kind that quietly do the repetitive work so people don't have to. Most of what's below started as a manual process someone was tired of repeating: sorting email, copying data between tools, tracking down which workflow changed and when.

When the automation needs more than a workflow canvas can give it (an API, a database, a scheduled job), I build that layer too, in Python, FastAPI, or Node.js, containerized with Docker and backed by Supabase or SQL.

Each project on this page is a modular demo, built with the same concepts and technologies used in production systems. If something here is close to a problem you're carrying, that's a good place to start a conversation.

Professional experience

career.log: most recent first.

  1. Software Developer

    [June 2024 → June 2025]

    Kaizo IT Solutions (Messaging Automation SaaS)

    • Contributed to a SaaS product that automated outbound customer messaging, working across a Python/FastAPI backend and React frontend.
    • Developed and maintained REST API endpoints in FastAPI supporting message scheduling and delivery features.
    • Built React UI components that enabled users to configure and monitor automated messaging campaigns.

What clients say

I worked with Kyle. He is very attentive to detail and ensures that he meets clients' expectations.
Miguel Saul Project Manager, Kaizo IT Solutions
next-step.sh

Let's build your next automation.

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