Refact.ai

Refact.ai is an open-source AI coding agent built for individual developers, engineering teams, and enterprises who want to accelerate software development without surrendering control of their source code. It works directly inside the IDEs developers already use, combining real-time code completion, an in-editor chat, and an autonomous agent that can carry multi-step engineering tasks from planning through testing.

How It Works

Refact.ai analyzes your repository using retrieval-augmented generation (RAG), drawing context from your codebase, documentation, and project structure so its suggestions reflect your actual patterns, libraries, and APIs. Developers can connect multiple large language models, choosing between providers such as Anthropic Claude, OpenAI GPT, Google Gemini, and others, or bringing their own API key. The autonomous agent can plan a task, edit multiple files, run code, and iterate on the results within the editor.

Key Features

• Autonomous agent: Plans and executes complex, multi-file engineering tasks step by step, including writing, debugging, and testing code.
• Code completion: Provides real-time, context-aware autocomplete suggestions as you type.
• In-IDE chat: Lets you ask questions, generate code, and get explanations in plain language without leaving the editor.
• Repository awareness: Uses RAG to understand the whole codebase rather than only the open file.
• Multi-model support: Works with several LLM providers and supports bringing your own key.
• Tool integrations: Connects with GitHub and GitLab, databases, Docker, and CI/CD pipelines for end-to-end workflows.

Supported IDEs and Languages

Refact.ai integrates with VS Code and the JetBrains family, including PyCharm, WebStorm, IntelliJ IDEA, GoLand, and CLion, alongside additional editors. It supports a broad range of modern programming languages and frameworks such as Python, JavaScript, TypeScript, Java, Rust, PHP, C++, and SQL.

Privacy and Deployment

Code privacy is central to Refact.ai. The project is open source, and teams can run it as a cloud service or self-host it on premises for full control over where code and data reside. Enterprise deployments add options such as private cloud hosting, model fine-tuning, and reduced telemetry, making it suitable for organizations with strict security or compliance requirements.

Pricing

Refact.ai offers a free plan that includes unlimited code completion, in-IDE chat, and limited access to the autonomous agent. A Pro plan is available at $10 per month with expanded agent usage and a larger chat context window. Enterprise pricing is custom and covers on-premise or private-cloud deployment, fine-tuning, and additional privacy controls.

Use Cases

• Speeding up day-to-day coding with context-aware completion and chat.
• Delegating multi-step tasks such as refactors, bug fixes, and test writing to the agent.
• Keeping proprietary code in-house through self-hosted or on-premise deployment.
• Standardizing AI assistance across a team while choosing the underlying model.