Dendrite provides an API-first toolkit that enables AI agents to interact with any website by simulating user actions such as clicking, filling forms, and authenticating without relying on traditional APIs. This technology addresses the challenge of accessing and extracting structured data from complex web environments, streamlining the development of web-based tools for automation and data collection.
Funding
Funding not disclosed
Founders
Product
Problem
AI agents often struggle to reliably interact with websites due to the limitations of traditional APIs and the complexities of modern web environments. Extracting structured data and automating actions on websites requires navigating dynamic content, handling authentication, and adapting to frequent layout changes.
Solution
Dendrite offers a developer toolkit that enables AI agents to interact with any website by simulating user actions, such as clicking, filling forms, and authenticating, without relying on traditional APIs. The toolkit provides a framework-agnostic approach to building web-based tools for automation and data collection, allowing agents to access and extract structured data from complex web environments. Dendrite leverages a Chrome Extension to securely share authentication sessions from the user's browser with the Dendrite client, eliminating the need to store login credentials. By developing workflows locally and hosting browser sessions remotely, developers gain fine-grained control over agent behavior and can seamlessly integrate Dendrite with platforms like LangChain, CrewAI, and LlamaIndex.
Target Audience
Dendrite targets AI developers and organizations building AI agents that require access to web-based data and automation capabilities across various industries, including social media, e-commerce, sales, and data analytics.
Features
- Simulates user interactions: clicks, form filling, keystrokes, file uploads/downloads
- Supports authentication on any website using a Chrome Extension for secure session sharing
- Enables data extraction as structured data, Markdown, or using Pydantic models and JSON schemas
- Provides natural language prompts for element selection
- Offers a TypeScript SDK and React chatbox plugin for rapid integration
- Allows local development for fine-grained control and debugging
- Supports remote hosting through Browserbase and Browserless
- Framework-agnostic design for compatibility with LangChain, CrewAI, LlamaIndex, and other AI agent platforms