SAFA.ai is an AI-powered tool that leverages large language models to automate the software documentation process. Its core functionalities revolve around the automatic generation and maintenance of software documentation, which enables engineering teams to save considerable time spent on manual documentation. It reads and understands code along with its related context while summarizing the contents of the code files in natural language. This gives a clear, concise communication about the behavior of a given code. Furthermore, SAFA.ai has the ability to extract the Abstract Syntax Tree (AST) from code files to provide a comprehensive understanding of the codebase. Beyond code summary, it handles higher-level system documentation such as User Stories, Requirements, and change logs, ensuring their updation as changes occur in the software. It also offers detailed change analysis by comparing different versions of a system, generating natural language summaries that describe how the system evolves over time. Another prominently beneficial feature is the provision of cross-documentation traceability. The system uniquely provides links across various documentation sources, codebases, and ticketing systems, resulting in an in-depth understanding of the entire system. With its system visualization and intelligent search features, exploring even complex software systems becomes substantially simpler rather than manually browsing through functions and files. SAFA.ai is designed to support multiple roles within a software team including engineers, project managers, QA Managers, and executives, providing them with essential insights, facilitating seamless team coordination, aiding in risk reduction, and enhancing cross-team communication.