JetBrains AI

What is JetBrains AI?

JetBrains AI is an advanced AI service embedded within JetBrains' suite of developer tools, designed to streamline software development by providing intelligent code assistance. It leverages multiple large language models from OpenAI, Google, and JetBrains’ own models to offer features such as code autocompletion, generation, explanation, and refactoring suggestions directly inside IDEs like IntelliJ IDEA, PyCharm, and Fleet. The AI Assistant understands project context and coding style, enabling developers to write, debug, and maintain code faster and with higher quality while ensuring data security and flexibility through on-premises model support.

Key Features

• Context-Aware Code Completion

  AI Assistant autocompletes lines, functions, and blocks of code tailored to your coding style and project context.

• Natural Language Code Generation

  Generate code snippets, tests, documentation, and commit messages from simple natural language prompts within the editor.

• Code Explanation and Debugging

  Explain code logic, runtime errors, SQL queries, and regular expressions, and suggest fixes and refactorings.

• Seamless IDE Integration

  Deep integration with JetBrains IDEs provides AI features in code editors, version control, and terminal windows for a smooth workflow.

• Data Security and Privacy

  Minimal data sent to AI models with no use of user data for training; upcoming support for on-premises AI models enhances security.

• Flexible Subscription Plans

  Offers Pro and Enterprise plans with scalable features including user management, on-premises deployment, and customizable AI models.

Use Cases

• Accelerated Software Development : Developers can speed up coding by leveraging AI-powered autocompletion and generation, reducing repetitive tasks.
• Improved Code Quality : Use AI to explain complex code, identify errors, and suggest refactorings to maintain clean and efficient codebases.
• Enhanced Collaboration : Generate clear commit messages and documentation to improve team communication and project transparency.
• Learning and Onboarding : New team members can understand codebases faster with AI explanations and contextual assistance.
• Multi-Language Support : Convert code between programming languages and generate tests to support diverse development environments.

FAQs