> For the complete documentation index, see [llms.txt](https://docs.kodesage.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.kodesage.ai/welcome-to-kodesage/introduction.md). # Introduction Kodesage Overview Welcome to Kodesage, the ultimate AI-powered code understanding tool designed specifically for enterprise legacy software ecosystems. Kodesage aims to revolutionize the way developers interact with complex legacy systems by integrating with multiple data sources including code repositories, issue trackers, wikis, and documentation. This comprehensive, context-aware knowledge base continuously updates, providing accurate and detailed system understanding, crucial for legacy systems. Kodesage supports developer workflows beyond coding, such as documentation, ticket creation, ticket analysis, task decomposition, estimation, and onboarding. By automating code documentation, enhancing code comprehension, and integrating with issue ticketing systems, Kodesage ensures robust security, high throughput, and low latency. It can be deployed both on-premises and to cloud environments, making it an ideal solution for enterprises with strict regulations or policies against sharing data with external cloud-based services. Kodesage supports developer workflows beyond coding, such as: * onboarding * documentation * ticket creation * ticket analysis * troubleshooting By automating these processes, Kodesage streamlines development tasks and enhances overall productivity. --- # 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 dynamically by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.kodesage.ai/welcome-to-kodesage/introduction.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 `build a script that syncs our docs to a CMS` 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.