Mantic is a context-aware code search engine focused on delivering relevant results rather than sheer speed. It has been tested on five major repositories, including TensorFlow and Chromium, showcasing its ability to produce higher quality results compared to traditional tools like grep and ripgrep. While Mantic may lag behind these tools in terms of speed for very large codebases, it compensates with better accuracy and relevance, particularly in complex queries. Key features include semantic reranking, which combines heuristic methods with neural learning to find relevant code even without exact keyword matches. Mantic also leverages Tree-sitter for deep codebase understanding, enabling functionalities like "Go to Definition" and "Find References." It remembers past queries to enhance its search capabilities and has introduced first-class support for Python. With the latest version, v1.0.25, it scans repositories like Chromium, containing 481,000 files, in under two seconds, effectively doubling its previous speed. Mantic's local-first design ensures privacy, with no data leaving a user's environment. It significantly reduces token usage by filtering out irrelevant files before searching. For teams of 100 developers, the cost of using Mantic is zero, in stark contrast to potential expenses for cloud-based solutions. The tool supports various command-line options for tailored searches, including session management for persistent context across queries. Overall, Mantic is designed for developers who prioritize search quality and relevance over raw speed, making it particularly useful in complex project environments.