Selected Work

What I've built

Sixteen years of enterprise AI and data work across Southeast Asia — banking, telecom, energy, retail, and government. Hands on the architecture and the delivery, and in the room when the business case gets made. Below is the shape of that work by sector, and the pieces of it that are public.

16+ Years in data & AI

$15M+ ARR driven

$30M+ AI value realized

40+ AI deployments

By sector

Government & Public Sector

National-scale citizen services where the constraint is rarely model quality — it is security posture, data sovereignty, and whether the thing can be operated in-policy once it is live.

Architecture and solution leadership for digital government workloads — primarily in Thailand, with regional exposure across ASEAN — spanning document understanding, citizen-facing assistants, and border-control modernisation. Several of these are published in the open (below).

AI sovereigntyAgentic AIDocument understandingPublic sector compliance

Banking & Financial Services

Where the modelling is rarely the hard part — getting the output into the channels and decisions that actually touch customers is.

Lead data scientist work on data-as-a-product platforms and their integration into customer-facing banking channels, shifting analytics from one-off reports toward reusable products other teams could build on.

Data-as-a-productCustomer analyticsPlatform thinking

Telecom & Digital Media

Subscriber bases large enough that a one-percent movement in segmentation accuracy is a material revenue number — and small enough modelling errors compound fast.

Segmentation and analytics leadership at national telecom scale, including founding a new analytics business unit and building micro-segmentation models that fed directly into commercial decisions.

Micro-segmentationAnalytics at scaleTeam building

Energy & Industrial

Heavy industry, where data is plentiful and messy and the cost of being wrong is measured in plant operations rather than click-through.

Senior data science work on energy-sector analytics.

Industrial analyticsEnergy sector

Client names, contract values, and architecture specifics stay out of this page by design. Where work is already published in the open, it's linked below.

Published work

Published on the AWS Public Sector Blog — real deployments, described in the open.

Modernizing border control with digital arrival cards on AWS Cloud Jun 2026
Digital government at national scale — throughput, security, and the operational realities of a border-control system. Co-authored.
Empowering government document understanding with Amazon Nova Multimodal Embeddings 2026
Multimodal AI applied to the unglamorous, high-volume document processing that most government workflows actually run on.
KMITL transforms prospective student guidance with Amazon Bedrock 2025
A generative-AI student advisor built for a Thai university, with the architecture described in the open.
Empowering bacterial genomics education with Amazon WorkSpaces 2025
Research and education computing — making genomics tooling reachable for students without local infrastructure.

Books

Two books published in 2026, both drawn from the same body of work — details and buy links.

Why Your AI Agent Will Fail
309 pages on why enterprise agent projects stall before production, and the decisions that separate the ones that ship. 30+ case studies across six industries.
REPLACED
What AI actually does to mid-career professional work — written from the builder's side of the table.

Writing & speaking

I write regularly here on architecture patterns, AI strategy, and the gap between demo and production — and speak at government, education, and industry events across Thailand. Read the articles or see the full speaking history.

Get in touch

I'm open to speaking engagements, consulting, and ghostwriting for executives and organizations. And always happy to talk about enterprise AI generally — what's working, what isn't, and why so much of it stops at the pilot stage.

hello@satsawat.ai LinkedIn

All views expressed here are my own and do not represent the views, positions, or policies of any current or former employer, client, or organisation I am or have been affiliated with.