Identity
Unverified · 0 matching sources · 2026-06-30No accepted supporting source is recorded for this field.
Agenova records Refact.ai as a coding agents product from refact.ai. No capability, pricing, or deployment field currently has publication-qualified Evidence; those claims remain Unknown.
Agenova verified this product identity, but accepted official evidence is currently insufficient for specific capability, pricing, integration, deployment, privacy, or enterprise-control claims. Unverified fields remain Unknown.
Refact.ai is an open source autonomous coding agent that handles engineering tasks end to end from inside the editor. Created by SmallCloud AI, it plans a task, searches the repository for context, edits files, runs tests, and iterates until the work passes, rather than only suggesting the next line. It has ranked as the number one open source agent on the SWE-bench Verified leaderboard, autonomously solving 352 of 500 real world GitHub issues, with the full benchmark pipeline open source so results can be reproduced. In everyday use a developer describes a task in natural language and the agent carries it out. The agent runs multi step and is capped at thirty autonomous actions per task, breaking work into steps, proposing and applying patches, running self tests, and revisiting earlier steps when something fails. It uses a Rust engine that keeps abstract syntax tree and vector indexes of the codebase current, and calls tools like symbol and semantic search and a debugging sub agent that runs and modifies scripts to find the cause of a failure. Because developers want oversight, Refact supports manual overrides: you can delegate a task and still preview and guide the process, review patches before they apply, and scope which files the agent can touch. Refact runs in VS Code, JetBrains, Visual Studio, Neovim, and Sublime Text, pairing the agent with unlimited free code completion from a built in Qwen model and retrieval over the project. It integrates with GitHub, GitLab, Docker, PostgreSQL and MySQL databases, continuous integration pipelines, a browser tool, and the Model Context Protocol, so it can create a branch, implement an endpoint, run tests in a container, and open a pull request from one prompt. Models are open: bring your own key for OpenAI, Anthropic, Gemini, DeepSeek, OpenRouter, or a local model, routed through an OpenAI compatible gateway at no extra platform cost. Its strongest pitch is control. Refact is fully open source under a permissive license and can run entirely self hosted, on premises or in a private cloud, with zero telemetry so code never leaves the customer's servers, plus file level access controls, audit logs for data access, and fine tuning on the team's own codebase, a practical option for security conscious and regulated teams. Pricing is coin based: a free tier includes unlimited completions and agent access with a monthly coin allowance, paid plans start around ten dollars a month, and bringing your own key runs the agent at no coin cost beyond the provider's charges. The original open source repository is now a legacy archive, with development continuing in a successor repository.
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0 of 8 decision fields supported. Evidence coverage is not a product score.
Known identity and product metadata appear below. The eight decision fields remain Unverified until accepted evidence supports them.
Request evidence →Documented product facts and Source-Backed claims do not establish execution quality or performance. Only publication-approved execution evidence can create an Execution-Verified state.
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