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Find where AI is worth it
Short audit: we walk your operations, rank ideas by payoff and hassle, and name what to skip. You leave with a plain list—not a 80-page strategy PDF.
AI Technology Advisor · Application Architect · Enterprise Systems
I help you turn AI from a buzzword into something your team actually uses.
Kevin Myat — AI Technology Advisor · Application Architect
Designing intelligent systems, modern platforms, and AI-enabled products.
Since 2016 I have built and shipped web apps, cloud systems, and remote teams. I work with founders and operators who are tired of AI pilots that never leave the demo—and want working software tied to real numbers: hours saved, fewer mistakes, faster handoffs.
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Years building software for real users
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Typical target for something live you can test
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Discovery sprint before we commit to a build
What I help with
Four ways to engage—same goal: less manual work, clearer decisions, software that survives Monday morning.
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Build AI that does real work
Internal tools, APIs, dashboards, and automations—wired with clear ownership, human approval where it matters, and logs you can defend to leadership or compliance.
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Connect the tools you already use
CRM, spreadsheets, case systems, Slack, Power Automate, whatever your business runs on. AI sits inside that flow—not beside it in a tab nobody opens.
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Coach your team & fix the basics
Workshops for leadership, sensible guardrails for staff using AI, and proper versioning for prompts so “quick fixes” do not break production on Friday night.
How we work together
Simple phases—no endless discovery theater.
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Listen & map (about two weeks)
Talk to the people doing the work. See the data. Draw the current process on one page. Decide the single best place to start—and what we are not doing yet.
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Build something real (30–60 days)
Ship in small slices your team can try. Each slice ties to a number you already care about: time to release, cost per transaction, error rate, support load—whatever you report today.
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Stay until it sticks
Training, tweaks, measurement, next improvement. Success means the tool feels boring—because people rely on it and leadership can see the before/after.
How I design AI systems
Not a single “bot.” A full stack your engineers, operators, and leadership can own—web, cloud, data, and AI in one coherent picture.
Reference stack — what I help you define and build
AI sits inside your product and platform—not as a floating chat window. Each layer has an owner, a diagram, and a way to test it.
Engagement flow — from first conversation to something measurable
Align on the business problem→
Architecture on one page→
Software on your cloud→
Rollout & guardrails→
Metrics you already trust
How I work
01
Results, not presentations
If we cannot point at hours saved or errors avoided, we are not done.
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Ship in weeks
Small live releases beat a nine-month roadmap nobody follows.
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Plain language
If your ops lead cannot explain it, it is not ready.
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Your tools, your data
Models change; your process and records should still make sense.
Architecture — buildings & systems
I design software systems, not buildings—but the habits are similar: start from necessity, make the structure honest, and care about what people experience when they use it.
“Success is a collection of problems solved.” — I.M. Pei · how I think about shipping
- Necessity first — What must work Monday morning, before any flashy AI demo.
- Old + new together — Your existing tools stay; AI connects to them instead of replacing everything.
- Visible structure — Clear diagrams and audit trails—no black box you cannot explain.
- Small wins that add up — Ship slices, measure, then widen—same spirit as the stack and engagement flow above.
Four layers I keep in every design
- Experience — What staff and customers feel (speed, clarity, trust).
- Structure — Services, APIs, databases, queues—drawn so a new engineer understands it in one whiteboard.
- Foundation — Security, backups, ownership of data, contracts with vendors.
- Light — Observability: logs, metrics, and the one dashboard that answers “is it working?”
Tell me what you want off your plate
30 minutes, no pitch deck. Describe the messy process and we will see if there is a sensible first build.
Kevin Myat (Kevin Moe Myint Myat)
Based in Asia-Pacific · working with teams globally
Builder — shipped systems
Nine years of client delivery across gaming, fintech, healthcare, robotics, and manufacturing. Proof that the architecture work ships—not just slides.
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Selected work
TeleMafia, DT One, Healthy365, Sesto Robotics, Mercedes-Benz Financial Services, ams OSRAM—case studies on this site.
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Engineering archive (2016–2025)
Full syntax-era portfolio: technical essays, project deep-dives, and the systems behind the builder chapter.
Writing
Short essays—technical, but meant for humans. All posts →
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The model is not the product
A chatbot is not a product. Here is what actually changes day-to-day work.
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Prompts are code you forgot to version
Treat prompt changes like code releases—so one “small fix” does not break production.
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Agents need a floor, not a ceiling
Before you give AI more freedom, decide what it must never do on its own.