Enterprise AI Vision
Multi-camera computer vision that turns noisy visual signals into clear operational decisions.
Tech Lead AI Systems Builder
I turn factory problems
into working systems.
I learned technology by staying close to real problems—and refusing to accept “that's how it has always worked.”
My work sits where software, hardware, AI and people meet. I move from observation to prototype quickly, then turn what works into systems that teams can operate, improve and own.
Today I lead builders across software and automation while remaining hands-on enough to challenge architecture, assumptions and outcomes.
Started by solving the next useful problem.
Building teams and systems across real operations.
Making intelligence a practical operating layer.
Software is only one layer. The outcome comes from connecting process, data, devices, intelligence and ownership.
Multi-camera computer vision that turns noisy visual signals into clear operational decisions.
Approval, visitor, access and action systems shaped around how factory teams actually work.
A local-first AI layer for translation, knowledge, governance and practical internal agents.
RFID, Android and automation tools that connect physical work with reliable digital records.
My default is not “add more.” It is to find the constraint, remove noise and build the smallest loop that creates learning.
The useful requirement is rarely the first request. Watch the bottleneck, the workaround and the human cost.
Reduce the idea until one small release can prove or kill the most important assumption.
A system is done when the work becomes clearer, safer or faster—not when the presentation looks complete.
I am interested in practical AI, factory systems, automation, technical leadership and ideas that look slightly impossible at first.
Start a conversation ↗TAY NINH · VIETNAM · OPEN TO USEFUL CONVERSATIONS