When people think about AI expansion into new markets, Japan doesn't always top the list. The narrative tends to focus on population decline, a cautious enterprise culture, and companies that take their time before adopting new technology.
That narrative is wrong. Or at least, it's incomplete.
We recently sat down with Nikkei Asia in Tokyo to talk about TinyFish's expansion into Japan, and the conversation got at something that matters not just to us, but to anyone thinking seriously about where AI goes from here.
Here's a problem that doesn't get enough airtime: most AI models are trained on historical data. They're extraordinarily capable at reasoning, summarizing, and generating, but they're fundamentally backward-looking. Ask one what's happening at a port in Osaka right now, or what the crowd conditions are at a major transit hub today, and it will either make something up or admit it doesn't know.
At TinyFish, we've been building AI agents that can go out and get that information: navigating live websites, pulling from authenticated data sources, monitoring real-time feeds that conventional models simply can't reach. As our CEO Sudheesh Nair put it to Nikkei Asia: "Models have a backward-looking view into what we call the indexed web. There is a lot of information behind authenticated internet services, databases, social media and live systems that is not trained into the models."
That gap is exactly what we're built to close.
Japan holds something genuinely rare: decades of operational data from some of the world's most process-disciplined organizations, sitting in systems that haven't yet been connected to modern AI. Add to that an aging workforce, a deep automation culture, and corporations that have been running complex logistics and infrastructure networks for generations, and you have a market where the right kind of AI can create outsized value.
"Japanese companies are sitting on decades of history and data," Nair told Nikkei. "The question is whether they can use AI to modernize."
We think they can. And we're here to help.
In partnership with NEC Networks & System Integration Corp. (NESIC), we're launching an application that connects TinyFish's AI agents with more than 70 live information sources (sensors, public data feeds, news, and social media), powered by Anthropic's Claude model.
The initial focus is on two areas where real-time information is not a nice-to-have, it's a requirement:
Disaster preparedness. Japan has among the most sophisticated emergency infrastructure in the world. Our system can continuously monitor earthquake sensors, weather feeds, and public broadcasts, then synthesize that information into actionable alerts before events unfold.
Supply chain management. We're mapping live supplier networks, logistics routes, and raw material sources so procurement and operations teams can see their supply chain as it actually is, not as it was last quarter.
In a recent demonstration, the system analyzed live video feeds and multiple data sources to estimate crowd levels around Tokyo Station in real time, pulling in weather reports, TV broadcasts, and online sources simultaneously.
The AI industry, as Nair told Nikkei, is still in its "very early innings." The first wave was about foundation models. The next wave is about agents that can gather information and act on behalf of users in the real world.
Japan is one of the most demanding environments you can test that in. The infrastructure is complex, the data is rich, and the bar for reliability is high. That's exactly where we want to be.
TinyFish was covered by Nikkei Asia on June 5, 2026. The full article is available to subscribers at asia.nikkei.com.
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