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Augment Code Review

Augment Code is an AI-powered platform for agentic software development at organizational scale, designed to boost engineering throughput and reduce merge times.

shipped Jul 5, 2026paid
Domain rating75Monthly visits109K/mo
Augment Code — product screenshot

Why it matters

1Augment Code operates through autonomous AI agents that plan, build, and open pull requests.
2Its proprietary 'Context Engine' continuously indexes entire codebases at millisecond-level sync.
3The platform offers on-premise deployment options for large enterprise environments.
4Augment Code secured $252 million in Series B funding at a $977 million valuation.

About Augment Code

Business Model
Subscription SaaS
Usage Pricing
33% lower token cost across the SDLC per token
Platforms
Web, API
Target Audience
Engineering teams and organizations looking to enhance software development processes.

Specs

API Docs

View Documentation →

API Available

Yes, public API

overview

What is Augment Code?

Augment Code is an AI-native coding platform tool developed by Augment Code that enables enterprise software teams and professional software engineers to automate coding tasks through autonomous agents and deep codebase understanding. It is specifically designed for large enterprise environments, focusing on multi-repository complex codebases and enterprise-grade features like role-based policy enforcement and on-prem deployment options.

features

Key Features of Augment Code

Augment Code provides a comprehensive suite of features designed to enhance enterprise software development workflows. Its core functionality revolves around autonomous AI agents and a proprietary Context Engine that offers deep, real-time codebase understanding across complex, multi-repository projects. The platform supports the entire software development lifecycle, from initial task planning to deployment.

  • Unified agents platform for orchestrating AI agents across the SDLC.
  • Proprietary 'Context Engine' for millisecond-level codebase indexing and understanding.
  • Autonomous AI agents for planning, building, and opening pull requests.
  • Prism Model Routing for optimal AI model selection, reducing costs by 20-30% per task.
  • Support for multiple environments, including local and cloud deployments.
  • Human-in-the-loop escalation for critical judgment calls and approvals.
  • Role-based policy enforcement for enterprise-grade security and compliance.
  • On-premise deployment options for sensitive and regulated environments.
  • API availability for integration with existing developer environments and LLMs.
  • Integration with popular development tools such as Slack, GitHub, and Jira.

use cases

Who Should Use Augment Code?

Augment Code is primarily designed for enterprise software teams, software engineers, and developers operating within large, complex, and multi-repository environments. Its capabilities are tailored to address challenges in scaling software development, improving code quality, and accelerating delivery cycles.

  • Enterprise Software Teams: Automating coding tasks, feature implementation, and large-scale codebase migrations to boost engineering throughput and reduce merge times.
  • Software Engineers: Gaining deep codebase comprehension, navigating complex project structures, and receiving intelligent code review and debugging assistance.
  • Developers: Significantly reducing onboarding time for new engineers by providing immediate context, generating comprehensive documentation, and automating test generation.
  • DevOps and Security Teams: Enhancing code quality and security through intelligent code review, bug detection, PR automation, and assisting with security remediation.

how to use

How to Use Augment Code

Augment Code facilitates agentic software development by integrating into existing enterprise workflows, allowing AI agents to interact with codebases and development tools. Users typically configure agents to address specific development tasks, leveraging the platform's deep codebase understanding.

  • 1Integrate Augment Code with your Git repositories (e.g., GitHub) and CI/CD pipelines.
  • 2Define a development task or user story for an AI agent to address.
  • 3Monitor the agent's progress as it plans, builds, and opens pull requests.
  • 4Review agent-generated code and pull requests, providing human feedback or approval.
  • 5Utilize the Context Engine for deep codebase navigation and understanding during manual development.
  • 6Configure role-based policies and deployment options (cloud or on-premise) according to organizational requirements.

pricing

Augment Code Pricing & Plans

Augment Code operates on a paid, credit-based pricing model, which has been a point of discussion among users. While specific tier names and fixed monthly prices are not publicly detailed for all offerings, the platform emphasizes a '33% lower token cost across the SDLC per token' compared to alternatives. Historically, individual plans like 'Indie' and 'Standard' existed but have seen strategic shifts, with inline completions being sunsetted for these plans as of March 31, 2026, pivoting towards multi-agent orchestration products like Intent. Enterprise customers typically retain access to a broader feature set and custom pricing structures. Users have reported significant price increases under the credit system for power users.

  • Paid, Credit-Based Model: Usage is billed based on credits consumed, with a focus on optimizing token costs.
  • Enterprise Plans: Custom pricing and feature sets, including retention of inline completions and on-premise deployment options.
  • Developer Plan (Historical): Reported price increases and shifts in feature availability, particularly the removal of inline completions.
  • Token Cost Optimization: Claims 33% lower token cost across the SDLC per token.

Pros

  • +Outstanding contextual awareness and deep understanding of complex, multi-repository codebases via its 'Context Engine'.
  • +Autonomous AI agents capable of planning, building, and opening pull requests for feature implementation and refactoring.
  • +Flexible deployment options, including critical on-premise support for enterprise clients.
  • +Significant potential for productivity gains and reduced merge times, with reported timeline reductions for migration projects.
  • +Prism Model Routing optimizes AI model usage, aiming for 20-30% cost reduction per task.
  • +Effective for large-scale refactoring, bug fixing, and developer onboarding by providing immediate context.

Cons

  • −Credit-based pricing model has led to confusion, cost anxiety, and reported price increases for power users.
  • −Strategic shift resulted in the sunsetting of inline completions for Indie, Standard, and Legacy plans (as of March 31, 2026).
  • −Agentic workflows can be slow on larger tasks, with reports of frequent timeouts requiring manual retries.
  • −Some users have experienced service unavailability or unresponsiveness, impacting workflow.
  • −The company's stance on 'GhostApproval' (AI altering files outside sandbox) as 'expected product behavior' raises concerns for some users regarding agent autonomy and control.

Policies

Pricing Page

View Pricing→

Similar Tools

Augment Code vs Competitors

Augment Code competes in the rapidly evolving market of AI-powered software development tools, differentiating itself through its focus on agentic software development, deep codebase understanding, and enterprise-grade deployment flexibility, including on-premise options.

1
GitHub Copilot EnterpriseOn Stork

It offers an autonomous coding agent and deep integration within the GitHub ecosystem, providing organization-specific codebase understanding and context-aware pull request reviews.

While both target large enterprises and offer agentic capabilities, GitHub Copilot Enterprise is primarily a cloud-only deployment, whereas Augment Code explicitly offers on-premise deployment options. GitHub Copilot Enterprise also integrates natively with GitHub.com for chat and codebase understanding.

2
Tabnine EnterpriseOn Stork

Tabnine Enterprise provides an Enterprise Context Engine that learns an organization's unique architecture and coding standards, offering flexible deployment options including SaaS, VPC, or fully air-gapped on-premise.

Similar to Augment Code, Tabnine Enterprise strongly emphasizes enterprise-grade security, compliance, and on-premise deployment flexibility. It also offers centralized visibility and granular access controls across users and teams.

3
Sourcegraph CodyOn Stork

Cody excels in cross-repository search and understanding for massive codebases, leveraging Sourcegraph's code intelligence platform to provide context-aware chat and fixes.

Sourcegraph Cody focuses heavily on codebase comprehension and AI-assisted troubleshooting across complex, multi-repository architectures, supporting self-hosted deployments. While it offers AI assistance, its agentic capabilities for autonomous multi-step workflows might be less pronounced than Augment Code's focus on agentic software development.

4
Mutable AIOn Stork

Mutable AI is an AI-accelerated software development platform that provides 'infinite context awareness' of the entire codebase, generating auto-updating documentation and enabling AI-directed multi-file edits.

Mutable AI, like Augment Code, targets enterprises with features like role-based access control and on-premise support. It differentiates by emphasizing automated documentation and codebase understanding, alongside code generation and refactoring.

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