Everywhere is a desktop AI assistant designed to provide intelligent, context-aware assistance directly from your screen without requiring you to switch apps or copy text. Built with C# and Avalonia, it leverages advanced LLMs like OpenAI, Claude, Gemini, DeepSeek, and Ollama to interpret text, images, or errors visible on your desktop. Unlike traditional chatbots that require manual input, Everywhere captures context in real time—whether it’s an error message, a web article, or an email draft—and delivers instant, actionable responses. This tool is ideal for developers, researchers, and professionals who want to reduce context-switching while boosting productivity with AI-powered help wherever they are on their machine.
What You Get
- Context-aware AI invocation - Press a keyboard shortcut to activate the assistant over any on-screen text or UI element; no copying or screenshots needed.
- Multi-LLM support - Seamlessly switch between OpenAI, Claude, Gemini, DeepSeek, Moonshot (Kimi), Ollama, and custom endpoints without leaving your workflow.
- Integrated system tools - Access web browsing, file system, terminal, and Windows Everything search directly from the AI interface for dynamic context retrieval.
- Frosted glass UI with Markdown rendering - Enjoy a modern, translucent interface that renders responses in clean, readable Markdown format.
- Multi-language support - Fully localized UI and AI responses in English, Chinese (Simplified/Traditional), German, Spanish, French, Italian, Japanese, Korean, Russian, and Turkish.
Common Use Cases
- Troubleshooting system errors - When a Windows application crashes with an obscure error message, invoke Everywhere over the text to get a step-by-step diagnostic and fix without searching online.
- Quick summarization of technical articles - While reading a 10-page research paper, highlight any section and ask for a 3-point summary to save time without leaving your browser.
- Instant translation of foreign-language content - Encounter a Japanese or German technical document? Select the text and command ‘Translate this to English’ for real-time, accurate translations.
- Email drafting with tone adjustment - Write a casual draft and use Everywhere to transform it into professional business communication by saying ‘Make this sound more polished’ while the text is selected.
- DevOps teams managing remote environments - Use Everywhere to query system logs or terminal output directly from a remote desktop session, reducing the need for clipboard transfers and improving security.
Under The Hood
The Dearva-Everywhere project is a cross-platform AI-powered application framework built with C# and .NET, designed to integrate multiple AI providers through a unified abstraction layer. It emphasizes modular architecture, reusable components, and seamless deployment across operating systems.
Architecture
This project adopts a layered, modular architecture that promotes clear separation of concerns and extensibility.
- A well-defined abstraction layer separates AI logic from platform-specific implementations
- Modular organization enables independent development and testing of core components
- Clear boundaries between UI, business logic, and AI service layers enhance maintainability
Tech Stack
Built on modern .NET technologies with a focus on cross-platform support and AI integration.
- C# and .NET form the core development environment, leveraging Avalonia for UI across platforms
- Integrates with AI SDKs from Anthropic and Google, alongside Semantic Kernel for LLM orchestration
- Uses source generators for configuration management and MSBuild for cross-platform builds
- Extensive use of conditional compilation and runtime identifiers supports Windows, Linux, and macOS
Code Quality
The codebase reflects mature software engineering practices with an emphasis on reusability and system-level compatibility.
- Comprehensive test coverage across modules demonstrates a commitment to quality assurance
- Structured error handling and consistent naming conventions improve code readability
- Well-organized directory structure and type annotations support long-term maintainability
- Type safety is enhanced through source generators and configuration abstractions
What Makes It Unique
This project stands out through its innovative approach to AI provider abstraction and cross-platform deployment.
- Modular AI provider abstraction allows switching between OpenAI, Anthropic, and Google services with consistent interfaces
- Source generators reduce boilerplate and improve type safety in configuration handling
- Cross-platform build targeting with platform-specific runtime identifiers enables flexible deployment
- Custom SDK patches and extensions enhance core functionality while maintaining compatibility with upstream libraries