Factory AI
Autonomous coding agents (Droids) for agent-native development

Enterprise AI coding platform built for large, complex codebases
Augment Code genuinely stands out for large-codebase context: its Context Engine is a real system, not a thin wrapper, and it shows strong results on cross-file work and PR review for big monorepos. The main caveats are its October 2025 shift to credit-based pricing, which made costs less predictable and drew user backlash, and that it is expensive and overkill for solo devs and small teams; pricing tiers are also reported inconsistently, so verify directly.
Augment Code is an enterprise-focused agentic coding platform built around a Context Engine that semantically indexes very large codebases for cross-file and cross-repo awareness. It works across VS Code, JetBrains, a CLI (Auggie), and cloud Remote Agents, and emphasizes not training on customer code. It excels at large monorepos and system-wide refactors, but its credit-based pricing is less predictable and it is costly for small teams.
Augment Code is an AI coding platform built around deep codebase context. Its Context Engine performs semantic dependency-graph indexing of very large repositories, reportedly handling codebases in the hundreds of thousands of files, so that its completions, chat, and agents understand cross-file and cross-repo architecture rather than just the open buffer. This focus on scale is Augment's central pitch to professional and enterprise engineering teams. The product spans multiple surfaces: VS Code and JetBrains extensions for completions, chat, and agent-driven multi-file changes; cloud Remote Agents for longer or repetitive tasks like tech-debt cleanup and refactors; the Auggie CLI terminal agent; and automated PR review. Augment uses a multi-model architecture and emphasizes a privacy posture of not training on customer code across all plans, alongside an enterprise security stance. Augment moved from flat per-seat pricing to a credit-based model in October 2025, a change that drew notable developer backlash over cost predictability for heavy agentic use. Commonly cited consumer tiers run from an Indie plan around $20 per month up to Max around $200 per month, plus enterprise. The company has raised roughly $227 million in a Series B (with a total near $252 million and a reported valuation just under $1 billion). Augment is strongest for large, complex codebases and system-wide refactors, and is generally overkill and pricey for solo developers or small teams.
Augment Code is an enterprise AI coding platform whose Context Engine semantically indexes very large codebases for cross-file, cross-repo awareness. It spans VS Code, JetBrains, the Auggie CLI, and cloud Remote Agents, and emphasizes not training on customer code. It excels at big monorepos and system-wide refactors but is costly for small teams, and its October 2025 shift to credit-based pricing made costs less predictable.
Augment Code is an enterprise-focused AI coding company built around large-codebase context, with a multi-surface product spanning IDEs, a CLI, and cloud agents.
It has raised roughly $227 million in a Series B (total near $252 million) at a reported valuation just under $1 billion, with investors including Coatue and Sutter Hill Ventures.
The Context Engine performs semantic dependency-graph indexing across very large repositories, powering completions, chat, and agent-driven multi-file changes. Cloud Remote Agents handle longer or repetitive work, the Auggie CLI brings agents to the terminal, and automated PR review runs on GitHub.
Augment uses a multi-model architecture and states it does not train on customer code, with an enterprise security posture across all plans.
Professional and enterprise engineering teams working in large monorepos or multi-repo systems who need cross-file architectural awareness for refactors, onboarding, and maintenance.
Professional software engineers working in large, complex codebases who use the IDE, CLI, and agents daily.
Engineering managers, VPs of engineering, and platform leaders at mid-size to large companies.
Senior engineers, architects, and developer-productivity teams evaluating AI coding tools.
An enterprise engineering organization with large monorepos or multi-repo systems that needs deep codebase context for refactors, onboarding, and maintenance and can absorb usage-based pricing.
Roughly $227 million Series B, reported around 2025 (with Coatue as reported lead and Sutter Hill Ventures among backers), bringing total funding to about $252 million at a reported valuation just under $1 billion. Lead-investor attribution varies across sources.
Its Context Engine semantically indexes very large codebases (reportedly hundreds of thousands of files), giving completions, chat, and agents genuine cross-file and cross-repo awareness rather than just local context.
It offers extensions for VS Code and JetBrains IDEs, plus the Auggie command-line agent for terminal workflows and cloud Remote Agents.
It moved to a credit-based model in October 2025. Tiers commonly range from about $20 per month (Indie) up to $200 (Max), plus enterprise. Costs can be unpredictable for heavy agentic use; verify current pricing directly.
No. Augment states it does not train on customer code across all plans, and emphasizes an enterprise security posture.
It is designed for large, complex codebases and enterprise teams. Solo developers and small teams may find it overkill and expensive relative to simpler tools.
Side-by-side pages for pricing, features, and best-fit use cases.
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