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Augment Code

Augment Code

AI-Native
Best output quality
Most customizable

The agentic SDLC platform for loops

SOC 2 Type II
GDPR
HIPAA
EU AI Act: Limited
Public status page
+12
Autonomous
Last updated: Aug 28, 2026
Freemium
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augmentcode.com

Quick Answer

AI

Augment Code is an AI-native coding platform that automates repetitive Software Development Lifecycle (SDLC) tasks for enterprise engineering teams. It features agentic loops for code review, incident management, and ticket-to-PR workflows, leveraging a Context Engine for deep codebase understanding. The platform supports multiple LLMs and integrates with tools like GitHub and Jira. Best for engineering teams replacing manual processes with a secure, scalable AI-driven solution. Paid plans start at $100/month for up to 50 seats, with usage-based billing.

About Augment CodeAI

Augment Code is an AI-native coding platform for enterprise software engineering teams, offering powerful coding agents, deep codebase intelligence, and flexible automations. It enables teams to run standing loops for code review, incident management, and ticket-to-PR workflows. Augment Code supports various LLM backends and integrates with existing developer tools, providing a secure and.

AI-extracted from public sources. May contain errors. Methodology · Report an error
What Makes Augment Code UniqueAI

Augment Code focuses on "standing loops" for the Software Development Lifecycle (SDLC), where agents continuously handle repetitive tasks, and humans intervene at checkpoints. Its Context Engine provides semantic codebase understanding, and the platform supports both managed cloud sandboxes and on-premise deployments for sensitive code.

Decision Intelligence

Best For

AI
Enterprise engineering teams automating repetitive SDLC tasks at scale
Development teams seeking to accelerate code review and merge times
Security teams automating vulnerability remediation and incident response
Organizations modernizing large, complex codebases with AI-driven migrations
Engineering leaders aiming to improve team standards and onboarding efficiency with AI agents
Pricing Overview

Type

Freemium

Dimension Scores

· 6.4 avg

How good it is, across universal quality axes

Ease of Use4/10
Output Quality8/10
Value for Money6/10
Customization8/10
Support7/10
Integration1/10
Accuracy & Reliability8/10
Compliance & Data Protection6/10
Performance5/10
Task Completion8/10
Tool Use Correctness8/10
Planning Quality8/10
AI-analyzed from product data·Medium confidenceHow we score

Task Scores

· 7.4 avg

What it can do, on category-specific tasks

Context Understanding9/10
Bug Detection8/10
Test Generation8/10
Security Scanning8/10
Code Completion7/10
Code Explanation7/10
Refactoring7/10
Multi Language Support7/10
Performance Optimization7/10
Documentation Generation6/10

Scores are AI-estimated from publicly available data — not an independent test or a verified user rating. How we rank →

Capabilities
Code
Code Review
Automation
Agent
Memory
Data Analysis
Search
Browsing
LimitationsAI
  • -Requires technical expertise for setup and customization of agent workflows
  • -Business plan limits to 50 seats, requiring Enterprise for larger teams
  • -Usage-based billing on top of the flat monthly fee can lead to variable costs
  • -No explicit mention of a free tier for individual developers to try without commitment
  • -Relies on external LLM providers, incurring additional costs for model inference
Fit Score

Complexity

Advanced

Company Size

Medium
Enterprise

Team Size

Small Team
Large Team

Skill Level

Expert
Features
Agentic SDLC loops for continuous automation
Context Engine for semantic codebase understanding
Code review automation with first-pass reviews
Ticket-to-PR automation for end-to-end task completion
Vulnerability remediation loop for automated fixes
Incident response loop for investigation and context assembly
Sub-agents for specialized tasks like security audits and test writing
Resumable sessions with persistent conversation history and task state
Technical Capabilities
SDK Available
MCP Compatible
Multi-Agent
Human-in-Loop
Team Features
Webhook Support
Has Demo
Function Calling (unknown)
Sandbox Mode
Audit Logs
No Signup
Works Offline (unknown)
Requires Host App
Framework
MCP Server
Digital Employee

Deployment

Hybrid

Runs Inside

GitHub
A2A Protocol:
MCP
Authentication
Single Sign-On
OIDC
Okta
OAuth
Google
Developer Access
API
Public
Webhooks
Sandbox
Login required
HITL mode:
Approve
Compliance, Privacy & Trust
GDPR: Stated by vendor
SOC 2: Stated by vendor
Type II
HIPAA: Stated by vendor
ISO 42001: Stated by vendor
Trains on user data: No
Model isolation: Dedicated
Human review:
Recommended
Tech Specs
Max upload: 4 MiB
Response time (est.):
Moderate
MCP Servers:
GitHub
Linear
Jira
Notion
Gmail
Drive
Calendar
Sheets
Docs
Slides
Salesforce
Datadog

The Model(s) Behind It

Model details — extracted from public vendor sources by our pipeline (Smart Generator + A3 cross-referencing) or admin-entered. Shown as claimed by the vendor; not independently audited by Intelloro.

Model Weight Availability
Closed API (no weights)
Training Data Provenance
Not disclosed
Relevant to EU AI Act Art. 53 / Annex XI (GPAI)
Supported Tools
Code Interpreter
Terminal
File System
Web Search
RAG / Vector Search
GitHub API
Jira API
Slack API
PagerDuty API
Datadog API
CI Pipelines
Pricing details not available yet.

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User Reviews

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Who It's For
4 roles
Software DevelopersComputer ProgrammersWeb Developers+1 more
Platform, Content & Languages
2 content types
1 languages
CodeTextEnglish+6 more

Output Languages

English

Content Types

Code
Text

Accepts

Code
Text
URL

Produces

Code
Text
JSON
Languages: English

Frequently Asked Questions

Video

Trust Score

90/100

Excellent

Based on 14 data signals

Confidence: High

Reflects publicly available data, not an independent audit

Compliance & Verified28/38
GDPRYes
SOC 2Yes
HIPAAYes
EU AI ActYes
Human ReviewYes
Human-in-the-loopYes
HITL TypeYes
Operational35/35
Status PageYes
Data ResidencyUS
Market Proof10/10
Notable CustomersAdobe, MongoDB, Pure Storage
Company17/17
Company ListedYes
Team Size51-200
User Base100K-1M
FundingSeries B
Health

Not yet checked

AI-Assisted Data

Some details are AI-generated estimates — verify with the vendor.

AI-generated estimate: Best For, Description, Limitations, Quick Answer, What Makes Unique

How we source data

AI Governance & Regulatory Disclosures

Legally-sensitive fields — extracted from public vendor sources by our pipeline (Smart Generator + A3 cross-referencing) or admin-entered. Shown as claimed by the vendor; not independently audited by Intelloro.

EU AI Act Risk Tier
Limited (Article 50 transparency)

Switching & Migration

Migration Difficulty
Significant Effort
Data portable as:
CSV
JSON
MD
Support:
Support Portal
Quick Stats
Agent TypeAutonomous
Base ModelClaude Opus 4.6 +10
PlatformsWeb, CLI, API +1
User Base100K-1M
LaunchedApr 2024
Company & Links

Company Name

Augment Computing

Founded

2022

Based in

United States

Last major update

Aug 2026

Funding

Series B · $252M

DocumentationChangelog