A / 00 — INDEX
§ Introduction

I've sat in the
CEO's office. I've done
the work on the floor.
I build AI for
everything in between.

I'm Note (Thanita S.), based in Bangkok. I build self-running businesses — AI systems that answer customers, run the routine, and report before you wake. Nine years and fifteen roles taught me exactly where to point them.

Most AI builders have seen one side of a business. I've lived on both — so my systems are built for the exact spot where the CEO's plan meets the team's Monday morning. That gap is where AI succeeds or fails. It's the only place I build.

Overnight log · my own operations — while I slept
No humans were involved.
Note (Thanita S.)
A / 01 — PORTRAIT
A / 02
Working motto
"The model is the engine. The system is the car. I build the car."
§ Section B — What I Do

Most people who build AI systems have never run one.

I have. Nine years across every department — in industries where decisions cost millions and bad information costs more. That's what makes the difference between a system that demos and one that holds.

B / 01 → 04
B / 01
Build
AI Chatbots
LINE OA + Meta Messenger. Reply in-brand around the clock, close simple sales, escalate the edge cases with full context attached.
For customer ops, sales
B / 02
Architect
Data Structure
A unified data layer that eliminates silos and connects your tools — so information flows between systems automatically, every team works from one source of truth, and decisions don't wait on whoever finds the right spreadsheet first.
For leadership, analysts
B / 03
Wire up
Automation
LINE-native chatbots and AI agents that handle conversations, route requests, and trigger the right actions — more capable than a static workflow, at a fraction of the cost of a new hire. Built on n8n and Make.
For ops, finance, HR
B / 04
Diagnose
AI Strategy
Two weeks of listening, mapping, and honest assessment. The output: a roadmap that shows exactly where AI earns its place in your workflow — and where a human still does it better. Designed for how your business actually runs, not how the demos look.
For founders, GMs
Tools of the trade
n8n· Claude· Airtable· Supabase· LINE OA· Make· Messenger API
C / 00
§ Section C — How I Work

Five steps, in this order, every time —
this is what an orchestrator actually does.

STEP 01
Map
I sit with your team and trace the workflow. Where is time going? Where is information stuck? Where would AI help, and where would it hurt?
STEP 02
Spec
We write what "done" looks like in numbers before writing any prompt. Evaluations come before code.
STEP 03
Build
The smallest system that closes the loop. Tools before prompts. Memory only when earned.
STEP 04
Watch
Every output logged and sampled. Every failure becomes a future test. Steady improvement, month after month.
STEP 05
Hand off
Runbooks, kill switches, dashboards. A system someone else on your team can own.
D / 00
Years in business
9+
since 2017
D / 01
Roles held
15
across every department
§ Section E — Background

Nine years at the CEO's side, with eyes on every department.

15 roles · 3 industries · 4 certs
E / 00 — Departments held
Fifteen roles, grouped
E.1 Earning Sales · Marketing · PR & Branding · BD · Customer Success
Taught me where revenue actually leaks — rarely where the CEO thinks.
E.2 Operating Operations · Supply Chain & Logistics · Procurement · PM
Taught me where time goes to die: handoffs, waiting, re-typing.
E.3 Money & People Finance / Accounting · HR / People
Taught me what breaks first when a business grows.
E.4 Data & Tech Data / Analytics · IT / Systems · Product
Taught me why dashboards get built and never opened.
E.5 Big Picture Strategy · General Management
Taught me how decisions really get made — and how slowly.

From the CEO's chair I learned what the plan wants. On the floor I learned why it fails. I build the AI that closes that gap.

E / 01
Industries lived in
Real Estate
Interior & Construction
Fashion / Design
E / 02
Education & certs
Fashion Design & Business
Raffles Int. College
Chinese Business & Trade
Capital Normal Univ.
Data Analytics Professional
Google
Data Analytics
IBM Certified
§ Section F — Selected Work

One flagship, two supporting acts.

F / 01 → 03
Names sit behind NDAs
01
The flagship
A business that runs itself.
Nine agents · one dashboard · zero meetings
F / 01
Problem One operator. Research, content, monitoring, follow-ups, reporting — a full day of routine work standing between her and the decisions only she can make.
System Nine specialized AI agents — each with a name, a role, and a schedule — coordinated from one command dashboard. One researches markets before sunrise. One drafts content. One watches the systems. One argues with the plan before reality does. They work through the night and report by morning.
Proof Not a client story — my own operation. I run everything I sell on myself first. Ask for the live tour.
02
F / 02
AI Chatbot, 24/7
LINE OA + Meta Messenger
Problem Team drowning in after-hours questions. Closing the laptop never closed the inbox.
System A conversational AI that answers in-brand, closes simple sales itself, and escalates only the tricky ones — with the full conversation history attached.
Result Customers answered around the clock. Team got their evenings back.
03
F / 03
Office Automation
Document parsing · report generation
Problem Hours every week disappeared into the same repetitive tasks — re-typing data, reading payment slips, assembling reports.
System A system that reads documents, files things, generates the weekly summary, and runs every night without supervision.
Result Several hours of every team member's week, returned.
G / 00
§ Section G — Now

What I'm doing this season.

Building
AI systems for Thai businesses. Busy in the best way.
Practicing
Writing under my own name.
Working with
Owners and executives who already know what to fix.
Walking
With Toni Stark & Rhaenyra. Every morning. Slowly.
Last updated 2026.07.12 · this page updates whenever it stops being true
G / 01 — NOW · 2026.07
I / 00 — TONI STARK
Companion

The one constant
in every good system.

Toni Stark is the grey shadow at my feet while I work. She has strong opinions about meeting length, walking pace, and which clients sound trustworthy. She is paid in walks. She has the best instincts of anyone in the office.

Toni Stark, supervising from the good chair
I / 01 — TONI STARK
K / 00
§ Section K — Contact

If anything here
felt familiar — let's talk.