John Anastacio
0 — Portfolio
Open to AI Solutions Engineer roles · select projects — Remote worldwide

Automation that thinks. Systems that scale.

John Anastacio — AI Solutions Engineer. I build AI agents that run real operations, and prove they work before you trust them with anything: source-cited answers, tested failure paths, and a human gate on every call the system shouldn't make alone.

↗View selected work →Claim my Free Audit
Scroll

John Anastacio is an AI Solutions Engineer based in Central Luzon, Philippines, open to full-time AI Solutions Engineer and Solutions Architect roles and select projects, remote worldwide. He builds RAG pipelines, AI agents, self-running CRM systems, and end-to-end workflow automation with a focus on data integrity: source-cited retrieval, failure-path testing, confidence-gated learning, and vector stores kept in sync with source documents. Stack: n8n, GoHighLevel, Zapier, OpenAI, Anthropic Claude, Claude Skills, Google Vertex AI, Gemini, RAG, vector databases, Pinecone, Supabase, API and webhook integrations, plus Python and FastAPI backends shipped on Docker, nginx, and Oracle Cloud with pytest suites and GitHub Actions CI. Background in enterprise IT infrastructure, presales solutions engineering, and systems administration.

0+
automations deployed across n8n, GoHighLevel, Zapier, Make, and custom systems.
0
years debugging infrastructure and scoping impossible projects before automating them.
−0%
research time on a legal RAG system — with audit-ready, source-cited answers on every query.
Selected Work

Curated
automations.

Selected projects and proof of concepts. Real systems, real results.

01

Dual-RAG Support Agent + Self-Syncing KB

Support agent on Google Vertex AI (Gemini) that answers only from an authoritative knowledge base, over dual Pinecone retrievers — company docs plus self-learned Q&A. Confident answers are learned behind a confidence gate; hard cases escalate to a human. A Drive-watch pipeline upserts and deletes vectors via Pinecone REST as source docs change, so answers never drift from the source of truth. The agent prompt was tested on its failure paths — off-topic, empty, partial, and citation-bait inputs — and held on all four, with citations verified against the source documents.

Self-maintaining, escalation-safedocs change → vectors sync → answers stay current
4/4Failure-path tests held
2Models, consistent behavior
n8nVertex AI · GeminiPineconeGoogle Drive
02

Document Intelligence RAG System

AI-powered knowledge base for a legal firm — lawyers ask questions in plain English and get source-cited answers in seconds, fully audit-ready on every query.

−71%research time per query
<3sAvg query response
1,000+Pages indexed
100%Source-cited outputs
n8nPineconeSupabaseRAG
03

GHL Sales Funnel — Bloom Dental Studio

The system automated lead capture, appointment scheduling, confirmations, reminders, and follow-ups — helping increase conversion rates and reduce no-shows. It also included targeted consultation-stage upsell automation to improve whitening treatment acceptance and increase revenue per patient. All automations and the site itself were built on HighLevel.

Higher conversion, fewer no-showscaptured → booked → upsold
HighLevelFunnelsCalendarsSMS & Email
04

AI Job Scraper & Resume Optimizer

Search freelance jobs from Slack with custom keywords. Matching positions are scraped, analyzed, and rewritten into a tailored resume via NVIDIA NIM — then auto-saved to Google Workspace with a Slack alert.

Slack-triggered, end-to-endfully hands-off
<90sPer resume optimization
100%Matching jobs customized
n8nNVIDIA NIMSlackGoogle Workspace
05

CRM Auto-Enrichment

Inbound contacts arrive via webhook, get enriched by Apollo + GPT, and land in GoHighLevel pre-qualified — with a sales brief and welcome email already sent before your team ever sees the record.

Pre-qualified before first touchwebhook → CRM
<2minAvg enrichment + email send
100%Contacts enriched
ZapierGoHighLevelGPTApollo
Reliability

How you'll know
it actually works.

4/4 held

Tested on its failure paths

Off-topic, empty, partial, and citation-bait inputs — the support agent was tested against all four before it went anywhere near a user, and held on every one. Most agents are only ever tested on the questions they're expected to get.

100% source-cited

Answers you can audit

Every response carries the source document it came from. On the legal RAG system that's every query, verified against the originals — so a wrong answer is traceable in seconds rather than argued about.

Human gate

It escalates instead of guessing

Confident answers get learned behind a confidence gate; anything below it goes to a person. And when source documents change, the vector store changes with them — so the system doesn't quietly drift away from the truth.

What stays human

No agent I build sends a customer-facing message on its own, commits money, or resolves the edge cases it was never confident about. Those escalate — by design, not by accident. A scope that admits its limits is the only kind worth signing off on.

About

John Anastacio builds self-running systems that turn underused tech stacks into ROI-generating operations.

AI Solutions Engineer with almost a decade of experience in enterprise IT infrastructure and presales solutions engineering. I design and build RAG pipelines, AI agents, self-running CRM systems, and end-to-end workflow automation — for real estate agents, financial advisors, SaaS founders, and consultants.

My builds treat data integrity as a feature: source-cited retrieval, failure-path testing, and knowledge bases that stay in sync with their source documents — reliable, documented systems that keep working long after launch.

AI & agents

  • OpenAI · Claude · Gemini (Vertex AI)
  • Claude Skills & agent orchestration
  • Prompt engineering & failure-path testing
  • n8n, Zapier & Make

Data & RAG pipelines

  • Pinecone & vector stores
  • Supabase · Postgres · DuckDB
  • Embedding & ingest pipelines (CRUD sync)
  • Source-cited retrieval

Backends & APIs

  • Python · FastAPI services
  • REST & webhook integrations
  • Scheduled jobs & background workers
  • Telegram & Slack bot interfaces

Ship & operate

  • Oracle Cloud · Docker · nginx
  • systemd services & verified deploys
  • pytest suites & GitHub Actions CI
  • Health checks, alerting & runbooks

CRM & workflow

  • GoHighLevel
  • Pipeline design
  • Lead capture & follow-up
  • Auto-enrichment pipelines

Enterprise infrastructure

  • Fortinet · Palo Alto · HPE
  • NAS / SAN · VMware · Windows Server
  • SOPs, runbooks & change management
  • SLA management
Feb 2018 — Mar 2026
Presales Solutions Engineer
Concentrix · Philippines
Scoped and recommended network, server, and storage architectures across security, compute, and storage — from targeted upgrades to full-scale migrations for multiple clients.
Apr 2016 — Jun 2017
Windows System Administrator
Hewlett Packard Enterprise · Taguig
Managed enterprise IT operations across incident, change, and project management within strict SLAs in a multinational data center — authoring change requests and runbooks to standardize procedures.
Sep 2015 — Dec 2015
RIM Bootcamp — System Administration Training
Fujitsu Philippines Global Delivery Center
2010 — 2015
B.A.Sc. — Electronics & Comms Engineering
Polytechnic University of the Philippines
Methodology

How the work
actually gets done.

01

Discovery & Scoping

We find where your team is losing the most time and agree on exactly what success looks like before anything gets built.

02

Architecture Design

You get a clear blueprint of how the automation works, what it connects to, and how it handles edge cases — no surprises mid-build.

03

Build & Iterate

Fast build cycles with regular check-ins so you can see progress, give feedback, and course-correct before launch.

04

Prove It Works

Before anything goes live, we agree on what "working" means in numbers — accuracy on your own real cases, what escalates to a human, and what happens when it's wrong. Then it gets tested against that, not against a demo.

05

Deploy & Sustain

You get a live system with full documentation — and an optional retainer for the work that keeps an agent honest after launch: monitoring, re-testing when models change, and tuning as your process moves.

Offers

Tailored
AI solutions.

Workflow Automation

One repetitive, time-consuming workflow — scoped, built, documented, and handed over. Best for small teams who want a specific bottleneck gone without a long agency engagement.

$2,500per project *
Most popular

AI Agent Build

An agent that runs a real process end to end — retrieval, decisions, escalation — with an accuracy target you sign off on before launch and a human gate on the calls it shouldn't make alone.

$5,000per project *

AI Consultancy & Scale

For teams running complex, multi-stage operations, or who need someone to work out what's worth automating before anyone builds. Scope and pricing shaped around the engagement — including ongoing agent operations once systems are live.

Customscope-dependent

* fixed price per project, with an optional monthly retainer for monitoring, re-testing, and tuning after launch · all engagements remote-first, worldwide

Built for your bottleneck,
not off-the-shelf.

Works with founders, ops leaders, and product teams who take automation seriously — and want it built once, built right. Currently open to full-time AI Solutions Engineer / Architect roles alongside select projects.

Not sure it's a fit? Answer 10 questions first →
Manila, Philippines · Available worldwide
SuMoTuWeThFrSa
· 30-min Free Workflow Audit