> For the complete documentation index, see [llms.txt](https://docs.chaingpt.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.chaingpt.org/overview/chaingpt-foundation.md). # ChainGPT Foundation ## Intro Welcome to the ChainGPT Foundation, where we house three innovative companies: ChainGPT AI, ChainGPT Pad, and ChainGPT Labs. ### Our Vision: At ChainGPT Foundation, we envision a future where advanced AI technologies power the decentralized Web3, blockchain, and crypto landscapes, making these technologies accessible, efficient, and user-friendly for everyone. *** ### **ChainGPT AI** A leading provider of AI-powered infrastructure for the crypto, blockchain, and Web3 industries. It offers automated smart contract generation and auditing solutions, autonomous community management, advanced Web3 AI Chatbots, AI-powered news aggregation, and NFT generation to improve the Web3 space for retail users and startups. ### **ChainGPT Pad** A platform designed to support promising Web3 projects that want to introduce tokens into their ecosystems and launch them via IDOs. It provides comprehensive support to ensure project success. ### **ChainGPT Labs** It offers extensive support to emerging Web3 projects, with investments ranging from $100k to $400k. It also provides strategic guidance, marketing expertise, and hands-on involvement, including incubation and an acceleration program. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.chaingpt.org/overview/chaingpt-foundation.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.