Taipei, Taiwan
AI development for Taipei teams, handed over in writing
One shop, Vancouver, British Columbia. Taipei sits on the other side of a full day, so nothing about this engagement runs on meetings. It runs on written handoffs, logged decisions and review that happens while the other side is asleep.
- base
- vancouver, bc, canada (UTC-08:00)
- market
- Taipei, Taiwan
- your clock
- UTC+08:00 (Asia/Taipei)
- overlap
- none on the same date, written handoff instead
- presence
- remote only, no office in Taipei
No shared working day, so the loop is written
Taipei is 16 hours ahead of Vancouver. When we start at 09:00 it is 01:00 on the next day for you, and when we stop at 17:00 it is 09:00 on the next day. On the same calendar date there is no hour where both sides are at work.
The honest version of this is a selling point. You get a full uninterrupted Vancouver day of work delivered as a written handoff, and we get your review waiting for us in the morning. Two shifts a day, no overtime.
- Everything built during our day lands in one written note before we close the laptop. No status meeting stands in for it.
- Your morning starts with that note and a set of pull requests to review, which is a better start than a calendar invitation.
- Every decision worth arguing about is written down where the code is, with the reasoning and the date attached.
- Questions come with a recommendation, because a question that needs a reply before work continues costs a full day here.
One live call a week, and it is scheduled honestly: 17:00 in Vancouver is 09:00 in Taipei on the next day. Neither side takes a bad hour for that one. The call simply lands on two different calendar dates, which is a scheduling detail rather than a hardship.
What Taipei buyers usually bring us
The record for Taipei lists two industries. Here is the part of each one that turns into an engagement, and the service line it lands under.
semiconductors
Verification and tooling repos are enormous and slow, so the first work is feedback speed and scoped rules, not a model upgrade.
It opens with an audit of where AI already helps in your repository and where it produces work your reviewers throw away.
Closest service line: Codebase and team optimization
electronics manufacturing
Yield data lives in reports and process changes live in email. Indexing them together is what turns a recurring defect into a searchable history.
Chunking follows the structure of the document instead of a character count, which is the whole difference between a useful index and an expensive one.
Closest service line: Knowledge bases and retrieval
Contracts, currency and where the data sits
Invoices are in US dollars. Hardware buyers here want the eval numbers before the demo, which suits how we work.
Everything else is the same as it would be for a client down the street from us: scope, a thin slice in week one, then weekly increments you can stop at any time. The distance changes the schedule, not the contract.
The five lines we sell
Same five lines everywhere, Taipei included. Most engagements are one of them, sometimes two.
- AI products, built end to end
- Knowledge bases and retrieval
- Codebase and team optimization
- Training and enablement
- Forward-deployed engineering
The languages, models and infrastructure underneath all five are listed on the Magic Ship stack page, with what each one is good for and where it is the wrong choice.
Other markets in Asia
Same treatment, different clocks, and in some cases a different answer.
Start a project
Send the problem. If it is a fit, you get scope and a timeline. If it is not, you get told that in the first reply instead of after a discovery process.