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Augment Code
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Coding (6)

Augment Code

Enterprise AI coding assistant with deep, real-time codebase context understanding

Last Update: 2026-07-26

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Starting price $100 per month

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Tool Information

What Is Augment Code?

Augment Code is an AI coding platform built for enterprises, powered by a highly secure, production-grade Context Engine developed over 2.5 years in stealth before its public launch. It semantically indexes an entire codebase, documentation, dependencies, and internal knowledge in real time, helping developers ship code faster, onboard in days instead of months, and modernize legacy systems with confidence.

Who Is the Owner of Augment Code?

Augment Code is developed by Augment Inc., headquartered in Palo Alto, California. The company is backed by major investors including Sutter Hill Ventures, Index Ventures, Innovation Endeavors, Lightspeed Venture Partners, and Meritech Capital, having raised a total of $252 million across two funding rounds.

Who Is the Founder of Augment Code?

Augment Code was co-founded by Igor Ostrovsky, former chief architect at Pure Storage and a former software engineer at Microsoft, and Guy Gur-Ari, an AI researcher formerly at Google. The company is led by industry veterans Scott Dietzen (CEO), previously CEO of Pure Storage, and Dion Almaer (VP of Product), an alumnus of Google, Shopify, Mozilla and Palm.

When Was Augment Code Launched?

Augment Inc. was founded in 2022 and operated in stealth mode for roughly 2.5 years before emerging publicly. The company came out of stealth in April 2024 alongside a $227 million Series B funding round, and officially launched publicly in November 2024.

Key Features of Augment Code

  • Context Engine: Semantically indexes an entire codebase, documentation, dependencies, and internal knowledge in real time for deeply context-aware suggestions.
  • Fast response times: Augment achieves around 200-300ms response times while maintaining full codebase awareness.
  • Autonomous agent workflows: Supports multi-agent systems that move beyond code completions into autonomous workflows, from feature builds to production incident response.
  • Code review: Includes AI-assisted code review capabilities as part of its enterprise workflow support.
  • Memories: The platform retains context across sessions to improve continuity in long-running engineering work.
  • Large-scale codebase support: Built to handle codebases of any size, from side projects to enterprise monorepos with millions of lines of code.
  • Legacy system modernization: Helps engineering teams confidently update and modernize older, complex systems.
  • Usage-based pricing model: Augment intentionally chose usage-based pricing over traditional seat-based pricing.

Best Use Cases of Augment Code

Augment Code is best suited for enterprises managing complex, multi-repository codebases that need deep contextual understanding rather than generic code completion. It's especially valuable for teams modernizing legacy systems, onboarding new engineers quickly, and adopting agentic workflows that go beyond the inner development loop into full software lifecycle automation.

F.A.Q (12)

Its Context Engine semantically indexes an entire codebase, documentation, and dependencies in real time, giving it deeper context awareness than typical code completion tools.

Yes, it's designed to work with codebases of any size, including massive enterprise monorepos.

Yes, its deep codebase understanding helps teams confidently update and modernize legacy systems.

Augment Code integrates with Visual Studio Code, all JetBrains IDEs (like IntelliJ IDEA), Vim, and Neovim, alongside a dedicated CLI agent for terminal-based workflows.

Yes, it offers native terminal and command-line integration through its Auggie CLI agent, letting developers work outside the IDE when needed.

Augment never trains its models on customer proprietary code, uses strict data minimization, and enforces access control so AI suggestions are only informed by code a specific engineer can access. It also uses a non-extractable API architecture and a Proof-of-Possession API to ensure completions operate only on locally possessed code, preventing data exfiltration and cross-tenant leakage.

Yes, Augment Code achieved SOC2 Type II attestation on July 10, 2024, following a rigorous three-month audit with no reported issues — a milestone the company notes GitHub Copilot had not reached at that time.

Yes, its security model is backed by customer-managed encryption keys and an ISO/IEC 42001-certified Artificial Intelligence Management System.

Yes, Augment Code supports single-tenant or VPC deployment options, which appeal to organizations with strict compliance checklists.

Augment Code's Context Engine can reason across 400,000+ files by indexing an entire codebase, while GitHub Copilot is optimized for fast, single-repo tasks and may lose depth on very large codebases.

GitHub Copilot supports multiple leading large language models (like GPT-4, Claude, and Gemini) so teams can optimize for speed, accuracy, or cost, while Augment Code focuses more on its proprietary Context Engine paired with select models.

Yes, GitHub Copilot supports agent-based workflows where it can autonomously handle issues, write code, and create pull requests, similar in spirit to Augment Code's multi-agent workflows.

Pros and Cons

Pros

  • Deep
  • Real-Time Codebase Context Engine
  • Fast Response Times (Around 200ms)
  • Built For Enterprise-Scale Monorepos
  • Semantic Indexing Of Docs And Dependencies
  • Multi-Agent Workflow Support
  • Usage-Based Pricing Instead Of Seat-Based
  • Backed By Major VC Investors
  • Team With Deep AI And Systems Engineering Pedigree

Cons

  • Usage-Based Pricing Can Be Less Predictable Than Flat Seat Pricing
  • Best Suited For Enterprises With Complex Codebases Rather Than Casual Users
  • No Long-Standing Free Tier Comparable To Competitors
  • Relatively New Entrant Compared To Established Coding Assistants

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Overview

Pricing
Paid
Platform
Web
Tool Type AI Coding Assistant and Agent Platform

Applicable Tasks

Code Completion Codebase Context Understanding Autonomous Coding Agents Code Review Legacy System Modernization Multi-Repository Support Enterprise Software Development
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