Refact.ai

Refact.ai suits developers who want an assistant connected to the code and tools involved in a task. Its agent can work with repository context, while chat and completion support smaller questions. Begin with read-only investigation of a reproducible issue. Database, browser and terminal connections widen what an agent can do, so make the permitted scope and expected checks explicit before allowing changes.

A practical workflow

1. Install a supported editor plugin and connect an approved project.
2. Choose the available model or provider connection.
3. Ask for an explanation and scoped repair plan.
4. Review changes and verify the original reproduction.

Illustrative input

This example describes a task, not a tested output. Adjust the source material and settings to your own situation.

Locate why this function returns a duplicate item. Explain the data path and propose the smallest fix with a relevant check.

Result check: Confirm the explanation against the code and inspect every affected file and command result.

Access and alternatives

The provider lists a continuing Free option with limited daily agent use, chat and completion, alongside paid Pro and enterprise offerings. Model choice, context size and agent requests vary by tier. BYOK and self-hosted configurations can require separate inference or infrastructure costs; self-hosting does not establish free hosted enterprise access.

Choose another workflow when its emphasis fits better: Tabby for another self-managed coding approach; Augment Code for a different repository-aware assistant.