TinyFish is a core infrastructure provider for the AI agent ecosystem, specifically addressing the "last mile" of web execution. While many companies focus on LLM reasoning or agentic memory, TinyFish focuses on the physical interaction between the agent and the internet. Their platform allows agents to perform actions that were previously blocked or prohibitively difficult to scale, such as logging into secure portals, handling dynamic forms, and navigating anti-bot defenses.
They are active in the stack as an execution engine and have significantly lowered the barrier to entry for building web-capable agents through their Mino API. Their support for the Model Context Protocol (MCP) and community integrations like n8n move them toward a "browser-as-a-service" model. For anyone building agents that need to do more than just read public text—agents that need to book flights, file regulatory reports, or manage insurance claims—TinyFish provides the necessary plumbing to make those actions deterministic and scalable.
TinyFish is built on a simple premise: the modern web was designed for human eyeballs, not LLM agents. When an AI attempts to navigate a dynamic website, it faces a gauntlet of anti-bot protections, captchas, and complex DOM structures that change without notice. TinyFish provides the infrastructure to solve this, offering a serverless browser grid that executes hundreds of operations simultaneously. Unlike traditional automation tools that are brittle and slow, TinyFish is designed for live execution on dynamic sites, allowing agents to navigate, authenticate, and transact in real-time.
The technical core of the platform is a fleet of remote browsers managed via a single API. This architecture shifts the burden of browser orchestration, proxy management, and anti-bot evasion from the developer to TinyFish. For an engineering team building a healthcare agent to track prior authorizations or a retail agent for dynamic pricing, this means they can focus on the logic of the task rather than the mechanics of the browser. The platform includes features like live execution streaming, which allows developers to watch agents work in real-time, and a "Workbench" for monitoring and debugging agentic flows.
Founded in 2024 and headquartered in Palo Alto, TinyFish is led by a team with deep enterprise roots. CEO Sudheesh Nair previously served as the CEO of ThoughtSpot and President of Nutanix, bringing a focus on enterprise-grade reliability to the AI agent space. He is joined by founders Keith Zhai and Shuhao Zhang, who have combined backgrounds in data science and large-scale systems. This leadership suggests TinyFish is not aiming for the casual tinkerer but for the enterprise stack where security and compliance are paramount.
In the competitive landscape, TinyFish sits between two worlds. On one side are the traditional RPA (Robotic Process Automation) providers like UiPath, which are often too heavy and slow for LLM integration. On the other are the web search APIs like Perplexity or Serper, which provide cached or "stale" data. TinyFish claims to solve the "7-of-7" capability checklist—offering fresh data, authentication support, parallel execution, production speed, cloud autonomy, reliability, and volume efficiency. They explicitly target the "93% of the web" that lies behind forms and paywalls, a segment often inaccessible to standard crawlers.
TinyFish uses a step-based pricing model, which is a departure from the traditional seat-based or request-based pricing of older web tools. This approach aligns costs with the actual complexity of the agent's task. Their Starter plan at $50/month covers 1,650 steps, while the Pro plan at $150/month scales to 16,500 steps and 50 concurrent agents. This "pay-as-you-go" structure, which includes LLM inference and residential proxies in the base price, simplifies the bill of materials for teams deploying agents.
Adoption is centered around complex, multi-site workflows. Case studies highlight health tech companies monitoring 50+ portals for insurance status and retail firms tracking pricing across thousands of e-commerce sites. By offering an MCP (Model Context Protocol) integration, TinyFish allows developers to plug their browser execution capabilities directly into LLM-powered IDEs and frameworks, positioning themselves as a fundamental utility in the agent developer's toolkit.
Enterprise infrastructure for AI web agents to navigate, authenticate, and automate workflows.
TinyFish is hiring