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Cursor offers local processing options where AI analysis happens on your machine rather than sending code to external servers. For enterprise users, there are on-premises deployment options and SOC 2 compliance features. You can configure which parts of your codebase are analyzed and control data sharing preferences. However, some advanced features may require cloud processing for optimal performance.
Cursor is designed to handle large codebases by intelligently indexing and caching project structure. It focuses on relevant context rather than processing every file simultaneously. However, initial indexing of very large repositories (100,000+ files) may take time, and performance can vary based on system resources. The editor includes settings to optimize performance for different project sizes and complexity levels.
Cursor analyzes patterns in your existing codebase to understand your preferred naming conventions, architectural patterns, and coding style. Over time, it adapts suggestions to match your team's standards. The AI considers factors like function structure, variable naming, comment styles, and framework usage patterns. However, this learning is project-specific and doesn't carry over between different codebases.
Cursor has strong support for popular languages like JavaScript/TypeScript, Python, Rust, Go, and Java, with particularly good framework support for React, Next.js, Django, and FastAPI. The AI's effectiveness varies by language — it is most powerful with well-documented languages and frameworks. Support for newer or niche languages may be limited, and domain-specific languages or custom frameworks may not receive optimal suggestions until the AI has sufficient codebase context to learn their patterns.
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Last verified March 2026