Tiny Fish

About Tiny Fish

Tiny Fish provides a platform that enables users to create AI agents for automating and enhancing everyday tasks through intuitive interfaces. This technology simplifies the process of task management, allowing individuals to increase productivity without requiring advanced technical skills.

```xml <problem> Extracting structured data from websites often requires writing fragile parsing scripts using technologies like XPath or CSS selectors, which are prone to breaking due to dynamic content and page structure changes. Existing web scraping methods can be time-consuming and require significant manual effort to maintain. </problem> <solution> AgentQL provides a suite of tools that leverage AI to connect large language models (LLMs) and AI agents to the web, enabling precise and scalable data extraction. The platform features a query language and parser that interacts with web page elements, extracting data quickly and accurately. AgentQL offers a robust alternative to traditional parsing methods by analyzing page structure using AI, ensuring consistent results despite dynamic content and page changes. The platform includes SDKs, a browser-based debugger, and a REST API for versatile integration into data workflows and automation processes. </solution> <features> - AgentQL query language for describing data extraction requirements without needing regex, XPath, or CSS selectors - Python and JavaScript SDKs for interacting with web page elements via Playwright and headless browsers - Browser extension for real-time query optimization on any web page - REST API for retrieving public-facing data from any URL without requiring a browser - PDF parsing capabilities for extracting tables and data from PDF documents - Self-healing queries that adapt to dynamic content and page structure changes - Reusable code that works across multiple similar pages </features> <target_audience> AgentQL targets developers, data scientists, and AI engineers who need to extract structured data from websites for web automation, scraping, and integration with AI applications. </target_audience> <revenue_model> AgentQL offers a tiered subscription model, including a free tier with limited API calls, a Professional plan at $99/month for 10,000 API calls, and custom Enterprise plans with fully managed solutions. </revenue_model> ```

What does Tiny Fish do?

Tiny Fish provides a platform that enables users to create AI agents for automating and enhancing everyday tasks through intuitive interfaces. This technology simplifies the process of task management, allowing individuals to increase productivity without requiring advanced technical skills.

Where is Tiny Fish located?

Tiny Fish is based in Palo Alto, United States.

When was Tiny Fish founded?

Tiny Fish was founded in 2023.

How much funding has Tiny Fish raised?

Tiny Fish has raised $9.3M.

Who founded Tiny Fish?

Tiny Fish was founded by Shuhao Zhang.

  • Shuhao Zhang - Co-founder/CEO
Location
Palo Alto, United States
Founded
2023
Funding
$9.3M
Employees
26 employees

Tiny Fish

10
Relative Traction Score based on online presence metrics compared to companies in the same age group.

Executive Summary

Tiny Fish provides a platform that enables users to create AI agents for automating and enhancing everyday tasks through intuitive interfaces. This technology simplifies the process of task management, allowing individuals to increase productivity without requiring advanced technical skills.

tinyfish.io1K+
Founded 2023 – Palo Alto, United States

Funding

No specific funding rounds found.

Total Funding

$9.3M

Team (25+)

Shuhao Zhang

Co-founder/CEO

Company Description

Problem

Extracting structured data from websites often requires writing fragile parsing scripts using technologies like XPath or CSS selectors, which are prone to breaking due to dynamic content and page structure changes. Existing web scraping methods can be time-consuming and require significant manual effort to maintain.

Solution

AgentQL provides a suite of tools that leverage AI to connect large language models (LLMs) and AI agents to the web, enabling precise and scalable data extraction. The platform features a query language and parser that interacts with web page elements, extracting data quickly and accurately. AgentQL offers a robust alternative to traditional parsing methods by analyzing page structure using AI, ensuring consistent results despite dynamic content and page changes. The platform includes SDKs, a browser-based debugger, and a REST API for versatile integration into data workflows and automation processes.

Features

AgentQL query language for describing data extraction requirements without needing regex, XPath, or CSS selectors

Python and JavaScript SDKs for interacting with web page elements via Playwright and headless browsers

Browser extension for real-time query optimization on any web page

REST API for retrieving public-facing data from any URL without requiring a browser

PDF parsing capabilities for extracting tables and data from PDF documents

Self-healing queries that adapt to dynamic content and page structure changes

Reusable code that works across multiple similar pages

Target Audience

AgentQL targets developers, data scientists, and AI engineers who need to extract structured data from websites for web automation, scraping, and integration with AI applications.

Revenue Model

AgentQL offers a tiered subscription model, including a free tier with limited API calls, a Professional plan at $99/month for 10,000 API calls, and custom Enterprise plans with fully managed solutions.

Sources:

1
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Tiny Fish - Funding: $9.3M | StartupSeeker