Augment Code

Augment Code is an AI coding assistant built for large real-world codebases, with deep repository context that powers accurate completions, chat, and agent workflows.

Overview

Augment Code’s differentiator is context: its retrieval system understands sprawling multi-repo codebases, so suggestions reference your actual patterns, APIs, and conventions rather than generic examples. It works inside VS Code and JetBrains as next-edit completions, inline chat, and a coding agent that can plan and execute multi-file changes. The context engine indexes dependencies and tests, helping the assistant propose changes that compile and pass CI, and a review mode summarizes diffs before merge. For enterprises, deployment options include strict data controls, retention settings, and self-hosted indexing, addressing concerns that generic assistants leak proprietary code. Engineers working in mature codebases often find the accuracy jump over context-shallow assistants substantial. Recent additions include background agents that handle routine tasks like dependency updates and test fixes, plus tighter integration with code review so AI-generated changes arrive with explanations a teammate can evaluate.

Key Features

• Repository-wide context engine spanning multiple large repos
• Next-edit completions tuned to your codebase’s conventions
• Coding agent for planning and executing multi-file changes
• Review mode summarizing diffs and flagging risk before merge
• Enterprise data controls with self-hosted indexing options
• Background agents handling routine maintenance like dependency updates and test fixes

Pricing

Augment offers a free trial period for evaluation. Individual and business subscriptions bill per seat with usage tiers, and enterprise plans add SSO, audit logging, and custom data-retention policies.

Who Is It For

Professional engineers working in large, mature codebases who want AI assistance that understands their architecture, and enterprises with strict requirements around proprietary code handling. It fits teams whose codebase is their core asset and who measure an assistant by whether its changes survive review and integration, not by how fast it types.