AI opportunity mapping
Find the decisions, delays, and repeated work where AI can create a real operating advantage.
OutputA prioritized opportunity map
AI for people who run things.
Clear notes on what's useful, what's noise, and what actually holds up — tested on my own companies first.
Seventeen-plus years running Litrad, JVT Corporation, and Halden Systems in the Philippines. Not a developer. Not a consultant. An AI forward deployment operator.
What I help with
Put AI to work where the work is.
The goal is not more software. It is a better way to operate: less friction, stronger decisions, and systems people will actually use.
Workflow automation
Turn one high-friction process into a focused pilot your team can test in the work itself.
OutputA useful system in the hands of users
Knowledge systems
Make scattered documents, expertise, and operating context easier to find, use, and improve.
OutputKnowledge that compounds
Team enablement
Give people the judgment, guardrails, and practice they need to use AI with confidence.
OutputCapability that stays with the team
How an engagement works
Start with the operation, not the model.
Diagnose the operating system
We map how the work actually moves, where it stalls, and what information people need to make decisions.
Build one useful pilot
We choose a narrow, valuable workflow and build the smallest version that can prove whether the idea holds up.
Embed the capability
We document the system, train the people around it, and define how the team will govern and improve it.
Built from the operator's side
Advice shaped by businesses, not a demo environment.
I have spent more than 17 years running businesses in the Philippines across trading, manufacturing, and infrastructure. Today, I test AI systems against the same constraints owners and teams face: incomplete information, busy people, and work that still has to ship.
That operator perspective keeps the work practical. We begin with the business problem, prove value in a real workflow, and keep a human accountable for the result.
Field notes
Learning in public.
Practical notes from applying AI to operations, knowledge, and adoption—what worked, what did not, and what changed my mind.
LATEST FIELD NOTES
3 entriesA useful place to start
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