EPORO TECHNOLOGY · AI ENABLEMENT · HONG KONG

Your business data lives in five systems,
and AI still isn't working for you?

Most companies don't lack AI tools. They lack a working path from data to results: processes that were never digitised, data missing the right dimensions, teams that don't know where to start, or tools that don't fit the job. Eporo finds the blocker — then helps you remove it.

About the AI Readiness Sprint One week on-site · Under NDA · Your data stays in your environment

When AI fails to land, it's usually one of these four

The first step of any diagnosis is turning "why doesn't AI work here" into specific, solvable problems.

PROCESS

Operations run on people, not systems

Key workflows live in WhatsApp threads, spreadsheets, and undocumented know-how — there's nothing for AI to plug into.

DATA

Data exists, but isn't usable

The systems hold data, but the dimensions, granularity, and quality can't support analysis or automation.

TEAM

Staff can't use it — or won't

Tools get bought, but nobody knows how to fit them into daily work. Two weeks later, they're abandoned.

TOOLS

The tool doesn't match the job

Adopting AI for AI's sake — with tools that don't touch the work that actually eats your team's time.

ENTRY ENGAGEMENT · AI READINESS SPRINT

The AI Readiness Sprint

Founding-client slots · 3 companies only

Pricing depends on your size and the scope of the diagnosis. You'll have a firm quote and timeline after the 30-minute intro call.

One week inside your day-to-day operations — watching how work actually flows, how data actually moves, and how your team actually spends its time. Not a questionnaire. How the week is structured (on-site vs. analysis) is something we agree together before we start, around your business.

  • A digitisation baseline across four dimensions: process, data, tools, and team skills
  • 3–5 prioritised improvement points, each with estimated cost and expected savings (hours / dollars)
  • Clear next-step recommendations — not a slide deck that gathers dust
  • If a suitable quick win surfaces during the week, I'll aim to validate it on the spot

NDA signed before we start · Analysis stays inside your environment · You end the week with a roadmap you can schedule and execute

Book a free 30-minute intro call

Built for two kinds of companies

One method, applied to different operating realities.

Cross-border e-commerce sellers

Multiple platforms, multiple ERPs, fragmented data — and an ops team drowning in repetitive analysis.

  • Multi-system data integration and automated reconciliation
  • Automated advertising and keyword analysis (Amazon Ads and beyond)
  • End-to-end efficiency across data → analysis → human review → campaign actions
Why me: As a Tech Lead at Amazon, I owned retail search and product-page backends, including a shared component driving an estimated $10M a year — I understand e-commerce from inside the platform.
Hong Kong SMEs

The business runs, but reports are assembled by hand and processes live in people's heads. AI feels relevant, but where to start?

  • Process digitisation and automated reporting
  • Getting your business data organised, connected, and governed
  • Staff training and embedding AI tools into real workflows
Why me: As a Senior Software Engineer and Tech Lead at Snowflake, I owned cross-cloud cluster provisioning and scheduling — enterprise data infrastructure was my day job for years.

About the founder

Jason Huang (黃嘉駿), founder of Eporo Technology, based in Hong Kong and working in English, Mandarin or Cantonese. Eight years building distributed systems at Amazon and Snowflake — the kind millions of people use every day.

At Amazon, as a Tech Lead, I built a closed-loop pipeline for search quality: a model makes the call, low-confidence results go to a human labelling team, and the new labels retrain the model. That taught me something that still holds — whether AI works inside a company usually has less to do with the model than with whether the handoffs between it and your people are wired up properly. In the same stretch I re-platformed the backend of a page carrying roughly 8.6 million customer visits a day, and built a shared widget framework whose best-performing component drove an estimated $10M a year.

At Snowflake, as a Senior Software Engineer and Tech Lead, I worked on the enterprise data platform itself — the layer companies worldwide trust with their most important data. I cut cluster start-up from about 7 minutes to 1.5, and took a data cleanup service to roughly 7× its throughput. But the more useful part for you is this: I consolidated 164 scattered system metrics into one dashboard people could actually read and act on. The problem inside companies is never a shortage of data — it's that the numbers disagree, nobody reads them, and when they do it still isn't clear what to do next. That is what I spent years fixing.

You might be wondering whether any of this transfers to a thirty-person company. The method does; the scale doesn't. What Amazon and Snowflake taught me was never "buy the most expensive tool" — it was measure first, then change one stretch of the process at a time. In a company of twenty people and a pile of spreadsheets that discipline pays off faster, not slower, because the bottlenecks are more obvious and the decision chain is shorter.

In the end it has always been the same job: find the most expensive stretch of a process, measure it, then make it shorter. I don't do generic "AI transformation consulting" — I start from your real data and real processes, find the highest-ROI steps, and help you build them.

The person you talk to is the person who does the work. I run the Sprint on-site myself — it never gets handed to a consultant or a junior.

Company
Eporo Technology Limited (Hong Kong)
Experience
Amazon Tech Lead · Snowflake Senior Software Engineer / Tech Lead
Tenure
8 years in distributed systems and cloud infrastructure
Education
UC San Diego, Computer Science
Focus
AI agent infrastructure · MCP · Data pipelines · LLM workflows
Languages
English · Mandarin · Cantonese
Public profile
LinkedIn ↗

Talk for 30 minutes first. Then decide.

The intro call is free. You describe where things stand; I tell you what I see — and if the Sprint isn't the right fit for you, I'll say so.

Email to book a call
EMAILjason.huang@eporo.ai
PHONE / WHATSAPP+852 5691 3731
LOCATIONHong Kong