TinyFish launches unified web platform for AI agents with Search, Fetch, Browser and Agent

On April 14, 2026, TinyFish unveiled something agent developers have long lacked: a single web infrastructure for AI agents that need to work with live sites rather than an archived copy of the internet. The company has put four layers under one API key: Search, Fetch, Browser and Agent, that is, search, content extraction, a remote browser and autonomous workflow execution. The idea is simple. Instead of stitching together several services for search, JavaScript page rendering, login handling and action automation, a team gets one platform with a common authentication method, a single credit pool and a predictable integration format.

The problem the release targets will be familiar to anyone who has tried to take an AI agent to production. Ordinary search is not enough when an agent has to find a competitor's current pricing page, open a heavy SPA interface, pull structured data from a dashboard or complete a multi-step flow on a real site. A typical stack combines separate search APIs, web scraping services, cloud browsers and custom orchestration.

TinyFish proposes slicing the task differently. Search returns ranked results and snippets as JSON. Fetch renders a page in a real browser and returns cleaned Markdown, HTML or JSON. Browser spins up a remote browser session for Playwright or CDP. Agent takes a goal in natural language and decides on its own where to click, what to fill in and what result to return.

Technically, the platform looks like an attempt to do for web automation what the unified API did for model access. In its documentation, TinyFish specifies a single `X-API-Key` header for all REST methods, support for a Python SDK, CLI and MCP integration, and compatibility with clients such as Claude Code and Cursor. The agent API has three modes: synchronous run, asynchronous run-async and streaming run-sse for applications that need real-time progress.

According to the documentation, a Browser API session is created in 10–30 seconds, while the company's homepage separately promotes stealth sessions and dynamic rendering support and claims a browser cold start of under 250 milliseconds. Fetch can process up to ten URLs independently in a single request, and Search is designed to return fresh results from the live web, not from a cache.

TinyFish is clearly betting not just on convenience but on production characteristics. The company claims its Web Agent reaches 89.9 percent accuracy on Mind2Web, and the Browser layer is aimed at sites with bot protection, login walls and dynamic interfaces. The references also cover per-country proxies, lite and stealth profiles and, for authenticated scenarios, a vault that connects to a password manager and passes credentials into a run.

According to the company, the infrastructure already serves hundreds of thousands of enterprise web agents per month and is used for tasks at Google, DoorDash, ClassPass and other large customers in hospitality, insurance, retail and logistics. That matters because the web agent market increasingly runs into not the quality of the model itself but resilience to real sites, timeouts, blocking and unstable markup.

Perhaps the clearest example of the platform's value is the insurance monitoring scenario TinyFish showed. One task is split across four layers: Search narrows the field to the relevant insurer pages, Fetch quickly grabs rate tables, Browser gets through protected sites, and Agent logs into portals, fills in forms and extracts the final quotes. On the service's showcase, this appears as a single pipeline that updates quarterly insurance offers and automatically flags premium increases above five percent.

The company also shows another case: an agent that logs into the booking system of a small hotel in Japan, reads dates and prices and updates the listing on Google Hotels without any changes on the hotel's side.

In practice, this means competition in the agent web stack is shifting from individual tools to a complete operational layer. If TinyFish can sustain the reliability and quality it claims under real production loads, developers will be able to spend less time stitching vendors together and more on the business logic of the agents themselves. Figures such as benchmark accuracy or the effectiveness of anti-bot bypass should still be treated as vendor claims and checked against your own scenarios.

But the direction is already clear: the AI agent market is maturing, and value is increasingly created not by yet another smart agent but by the infrastructure that gives it stable access to the live web.