TinyFish launched with the story of a small Japanese inn: hard to find online, often overlooked, yet full of value.
Why it matters: The web is messy. Hidden calendars, pop-ups, and shifting layouts break automation. General AI can “think” but rarely executes with reliability.
Our approach: TinyFish agents separate reasoning from doing. AI explores, rules execute. The result is observable, governed, resilient agents that run hundreds of thousands of checks daily.
The vision: If we can surface one tiny inn, we can unlock the web’s long tail. Technology should fade into the background so human work can shine.
We launched with a tiny Japanese hotel for a simple reason. Access.
An eight-room inn in the mountains. They don’t have a data team. No global distribution. Prices shaped by seasons, festivals, and which room catches the morning light. On the modern web, it slips out of sight.
We chose to start there.
Intelligence should not be a luxury. It should help the smallest operator show up with the same clarity as the largest brand. If an innkeeper cannot be seen, there is no choice. Only noise.
The challenge is technical. Hotel pricing is one of the messiest problems on the live web. Every site is different. Calendars render in odd ways. Pop-ups arrive at the wrong moment. Amenities shuffle. Content hides behind logins. Human brains glide through this. General purpose models do not. They reason well, then stumble on brittle execution.
We built for that gap. Our enterprise web agents separate thinking from doing. Models explore and adapt. We then codify what they learn into deterministic execution that runs at planetary scale. The system is observable. It keeps full logs. It respects governance. It survives script changes, bot defenses, shifting layouts, and reauthentication flows. The result is not just novelty, but outcomes.
That is why a traditional browser agent can take fifteen minutes to book a hotel, while our agents complete hundreds of thousands of price and inventory checks per day across tens of thousands of hotels. Same web. Different architecture. Reliable at volume.
This work is live with partners like Google. The interface looks familiar. The machinery underneath is not. If an agent can handle the long tail of hotels with consistency, it can handle the long tail of the web.
We picked the tiny hotel because it is honest. Everyone knows what it feels like to book a room. If we can make intelligence useful here, we can make it useful in healthcare, finance, retail, and the rest of the economy that still hides behind brittle interfaces.
Technology should feel quiet. It should clear the way for human work to matter.
That is our belief at TinyFish.
