World AI tech, read from Tokyo.

OUR LINE

Bilingual, not just translated.

Machine translation can read English. It can't ask 'does this make sense in Japan?' AITECH TOKYO is a bilingual editorial directory — not an automated feed, not a translation layer. We index the world's AI tech news every morning, pick the items a Tokyo business professional should know about, and translate them into Japanese with the editorial judgement a translator alone can't bring: which stories matter, which are press-release fluff, which deserve a line of context, and which are best summarised in one sentence and skipped.

OUR CITY

Why a Tokyo desk picks the lens.

AI tech is mostly written in San Francisco — for San Francisco. Launches assume US payment rails, English-only UI, and team structures built around Slack, Stripe, and venture capital. Japanese readers don't see any of this from a translated press release. AITECH TOKYO sits in the middle: bilingual enough to read the source, embedded enough in Tokyo's business reality to tell you which tools actually fit a Japanese workflow — and which ones assume an infrastructure you don't have. That second judgement is the layer machine translation will never deliver.

OUR METHOD

Four lines per story. Same four, every time.

Every entry in AITECH TOKYO gets the same four structured fields answered: a tagline that says what it actually is (not what marketing claims), the use case (who in Japan would actually use it and for what task), versus existing alternatives (ChatGPT, Notion AI, the raw OpenAI API, established Japanese tools), and the Tokyo Take — does this earn a slot in a Japanese workflow today, in Japanese, at a Japanese price, with a Japanese team structure? Same four questions, every entry. The press-release voice is left at the door, and the source is always linked.