TinyFishreview, pricing and verdict

Last updated: 2026-07-01

TinyFish is enterprise infrastructure that lets organizations run autonomous AI agents across external websites: logging in, filling forms, and extracting structured data without managing browsers or proxies. It scores 82 percent on the Mind2Web benchmark, well ahead of OpenAI's Operator, and already powers production traffic for Google Hotels and DoorDash.

About TinyFish

TinyFish is enterprise web agent infrastructure that launched from stealth in August 2025 with $47 million in Series A funding. It was founded in 2023 by Sudheesh Nair (former Nutanix President), Shuhao Zhang (ex-Meta engineering leader), and Keith Zhai (ex-Wall Street Journal), and enables organizations to automate complex web interactions at scale without managing browsers, proxies, or infrastructure themselves. The platform runs as a serverless API: it accepts a natural-language goal and a target URL, then dispatches an AI agent to navigate the site, handle logins and multi-step forms, extract structured data, and complete the transaction while streaming progress in real time. Traditional web scraping tools need CSS selectors, XPath, or custom configuration; TinyFish agents work from a plain-English task description instead, connecting to Claude Desktop through the Model Context Protocol and exposing a REST API, Python and JavaScript SDKs, and an AgentQL query language for developers who want more control. On the Mind2Web benchmark, TinyFish scores 82 percent versus 43 percent for OpenAI's Operator, a 39-point lead the company points to as evidence of production readiness rather than a research demo. TinyFish already runs in production at large enterprises: Google uses it to aggregate hotel inventory across Japan for Google Hotels search, DoorDash relies on it to manage web-interaction complexity, and ClassPass, Amazon, Amplemarket, NextEra, Jobright, and Healdev deploy it across healthcare prior-authorization tracking, insurance regulatory-filing monitoring, financial services, retail price monitoring, and supply-chain shipment tracking.

Pricing

Free: 500 steps, no credit card required. Pay-as-you-go: $0.015/step, 2 concurrent agents. Starter: $15/month (1,650 steps, 10 concurrent agents, $0.014 overage/step). Pro: $150/month (16,500 steps, 50 concurrent agents, $0.012 overage/step). Enterprise: Custom pricing with custom volume, concurrency, and SLA. All-inclusive: no separate charges for browsers, proxies, or LLM inference.

Key Features

• Parallel Web Automation: Run up to 1,000 simultaneous operations across multiple websites in a single deployment, enabling massive-scale web data operations without managing infrastructure.
• Natural Language Control: Describe web tasks in plain English—no CSS selectors, XPath, or code required. Agents interpret goals and execute workflows autonomously.
• Authentication and Dynamic Sites: Navigate password-protected sites, handle multi-factor authentication, interact with form-based systems, and extract data from JavaScript-rendered content at production speed.
• Claude MCP Integration: Connect TinyFish directly to Claude Desktop via Model Context Protocol, enabling AI assistants to run web automation with real-time progress streaming.
• AgentQL Query Language: Extract structured data and automate workflows using AgentQL, a specialized query language with Python and JavaScript SDKs, REST API, and browser debugger.
• All-Inclusive Pricing: No hidden charges for browsers, proxies, residential IP routing, or LLM inference. Step-based billing with transparent overage costs declining by tier.

Pros

• Benchmark performance beats OpenAI's Operator by a wide margin on the Mind2Web test, evidence of real capability on hard, real-world web tasks rather than a curated demo.
• Already running in production at recognizable big-name customers like Google Hotels and DoorDash, proof this has moved past pilot stage into everyday reliability.
• A free tier with no credit card required lowers the barrier for testing before committing budget.
• Plain-English task descriptions mean non-technical teams can automate a workflow without learning CSS selectors or XPath, unlike most scraping tools.
• All-inclusive pricing bundles browsers, proxies, and AI inference into one line item, simplifying budgeting against tools that meter each separately.

Cons

• CAPTCHA handling still limited; automated solving is not supported, blocking workflows on sites heavy in image-based or hCaptcha verification.
• Enterprise-only positioning with $47M in funding and a large-enterprise customer base means pricing and support are built around big companies, not individuals or small teams.
• API and MCP documentation is thinner than mature web-scraping tools, with fewer public recipes and integration examples published so far.
• The serverless architecture creates vendor lock-in: migrating a large workflow to a competitor or a self-hosted alternative would take real engineering effort.
• Step-based billing can be hard to predict since complex, multi-step sequences may cost more than a simple task estimate suggests.
• Success-rate, latency, and uptime SLAs are not published; enterprise buyers must request the details directly.

Visit TinyFish Official Website