Comparing as AI Code Generation & AutocompleteAugment Code vs Sourcegraph Cody
Augment Code
Sourcegraph Cody
Core Differences
- Architectural Foundation: Augment Code is a standalone, AI-native platform with a proprietary Context Engine that builds a semantic graph of the codebase from the ground up. It's designed as an end-to-end agentic system.
- Context Retrieval: Augment's Context Engine semantically indexes 400,000+ files to create a persistent, intelligent graph. Sourcegraph Cody leverages Sourcegraph's existing Code Search API to retrieve relevant code, symbols, and usage patterns from across multiple repositories. Cody relies on an established code intelligence platform, while Augment builds its own deep understanding.
- Workflow Focus: Augment emphasizes full SDLC agentic workflows (ticket-to-PR, automated review, incident investigation) through its Cosmos platform. Cody focuses more on developer assistance within the IDE (autocomplete, chat, inline edits) integrated with Sourcegraph's broader code intelligence features.
- Deployment & LLM Flexibility: Augment is primarily a closed-source SaaS offering, though Enterprise plans offer some cloud tenancy options. Cody offers admin-selectable LLMs (Claude, GPT, Gemini) and flexible deployment options including self-hosted or BYO cloud for air-gapped environments, providing greater control over infrastructure and model choice.
Verdict by Category
Best for Deep Codebase Understanding
Its proprietary Context Engine semantically indexes 400,000+ files, building a persistent graph for unparalleled cross-repo understanding.
Best for Enterprise Compliance/Security
It is the first and only AI coding assistant with ISO/IEC 42001 certification, alongside SOC 2 Type II, CMEK, and SIEM integration.
Best for LLM Flexibility
Enterprise admins can choose from Claude, GPT, and Gemini models without vendor lock-in, tailoring the AI to specific needs.
Best for Full SDLC Automation
Its Cosmos platform offers comprehensive agentic workflows from ticket creation to PR, automated code review, testing, and incident investigation.
Best for Deployment Flexibility
It supports self-hosted or BYO cloud deployment for air-gapped environments, offering greater control over data and infrastructure.
Best Value for Small Teams (up to 50)
Its Business plan offers a flat $100/month for up to 50 seats with pooled usage, making it more predictable and cost-effective than per-user models.
Editor's Take
Honest opinion from our review team
As an editor, I found that Augment Code's Context Engine truly impressed me with its depth of understanding. It felt like the AI wasn't just guessing based on my open files, but had a genuine, semantic grasp of the entire codebase, which translated into remarkably accurate suggestions and agentic outputs. The Cosmos platform's ability to take a ticket and progress it towards a PR felt less like a helper and more like a true autonomous assistant. While the initial indexing for large repos took a noticeable amount of time, the subsequent performance and accuracy were a clear payoff.
Using Sourcegraph Cody, on the other hand, felt like having an incredibly intelligent, multi-repository search engine deeply integrated into my IDE. Its seamless ability to pull relevant context from across dozens of remote repositories via Sourcegraph's platform was a significant productivity booster, especially in a sprawling enterprise codebase. The flexibility to choose between different LLMs (Claude, GPT, Gemini) was a definite highlight, allowing for task-specific model selection. However, the lack of a self-serve option or a free tier for individuals significantly hindered the initial exploration and quick adoption for smaller teams or individual developers outside of a formal enterprise procurement.
Detailed Comparison
The pricing models for Augment Code and Sourcegraph Cody reflect their distinct market positions and target audiences, with significant differences in accessibility and value proposition.
Augment Code utilizes a usage-based flat pricing model, with its Business plan costing $100/month for up to 50 seats. This includes a pooled usage credit for LLM inference, Context Engine API calls, and Cosmos compute. This model offers excellent value for small to medium-sized teams (up to 50 developers), as the cost is fixed, and usage is shared, preventing wasted spend on inactive users. Top-ups are pay-as-you-go, adding flexibility. However, it lacks a free individual tier, meaning solo developers or very small teams must still commit to the $100/month minimum. The Enterprise plan offers custom pricing with volume discounts and advanced features, requiring a sales contact.
Sourcegraph Cody, following its discontinuation of Free and Pro plans in July 2025, is now an exclusively enterprise-focused product. Pricing is negotiated directly with sales, but is reported at approximately $59/user/month on an annual contract. This makes Cody significantly more expensive on a per-user basis compared to Augment's pooled model for smaller teams, and also higher than many other AI coding assistants. The value here is tied to its deep integration with the broader Sourcegraph platform (Code Search, Batch Changes) and its deployment flexibility for large, complex organizations. The absence of any self-serve or free tier creates a high barrier to entry for individual developers or teams wishing to trial the product without a significant procurement process. For organizations already invested in Sourcegraph, the bundled packages might offer perceived value.
Augment Code Pros & Cons
Pros
- Deepest codebase context of any AI coding tool — Context Engine indexes 400K+ files with semantic graphs, not just open tabs
- #1 on SWE-bench Pro at 51.80% (Auggie CLI) — top publicly benchmarked coding agent score at publication
- First and only AI coding assistant with ISO/IEC 42001 certification alongside SOC 2 Type II and CMEK
- Usage-based flat pricing ($100/mo for up to 50 seats) is more predictable than per-seat models for variable teams
- Cosmos platform covers the full SDLC — from ticket to PR, code review, tests, incidents, migrations, and onboarding
- Trusted by Adobe, MongoDB, Webflow, Snyk, Pure Storage, Crypto.com, Tekion, and DXC across enterprise codebases
Cons
- No free individual tier — Business plan starts at $100/month with a team minimum; sole developers pay full price for low usage
- Pricing changed three times in 18 months (2023–2025), causing some developer community backlash and unpredictability concerns
- IDE support limited to VS Code and JetBrains — no standalone IDE, no Neovim full feature parity, no Visual Studio
- Closed-source with no self-hosting option — all computation runs on Augment's infrastructure or Enterprise cloud tenants
- Context Engine first-run indexing takes 15–30 minutes on large repos before initial suggestions become fully accurate
- Enterprise plan requires sales contact for pricing — no public list price above the Business tier
Sourcegraph Cody Pros & Cons
Pros
- Best-in-class multi-repository context — retrieves relevant code from across entire enterprise codebases, not just the open file
- Deep integration with Sourcegraph Code Search, Code Navigation, and Batch Changes for a unified code intelligence platform
- Admin-level LLM flexibility — choose Claude, GPT, or Gemini per use case without being locked to one model provider
- Guaranteed no-training on customer code with SOC 2 Type II, self-hosted, and air-gapped deployment options
- Trusted by over 1M engineers at Databricks, Plaid, Uber, Lyft, Reddit, GE, Dropbox, and Fortune 500 companies
- Engineers report saving 5–6 hours per week and writing code 2x faster according to Sourcegraph customer data
Cons
- Cody Free and Pro discontinued July 2025 — no self-serve individual tier; enterprise procurement via sales only
- Pricing starts at ~$59/user/month on annual contract, significantly more expensive than GitHub Copilot or Cursor for small teams
- Multi-repo context only works for codebases indexed in your Sourcegraph instance — disconnected repos are invisible to Cody
- No bring-your-own-key (BYOK) model access for individual users — model selection is admin-controlled at the enterprise level
- Requires Sourcegraph platform deployment — not a lightweight plugin for teams not already running Sourcegraph
- Sales-led procurement only adds friction for teams that want to trial the product quickly without a contract
AI Verdict
In the rapidly evolving landscape of AI-powered developer tools, Augment Code and Sourcegraph Cody emerge as two formidable contenders, both targeting large enterprise environments but with distinct approaches and core strengths. Augment Code, fresh out of stealth with significant funding, positions itself as an AI-native coding platform built from the ground up to tackle enterprise software engineering at scale. Its key differentiator is the proprietary Context Engine, a sophisticated system that semantically indexes massive codebases (400,000+ files), creating a persistent graph of functions, classes, and data flows. This deep, cross-repository understanding powers advanced agentic workflows via its Cosmos platform, covering the full Software Development Life Cycle (SDLC) from ticket creation to pull request (PR) generation, automated code review, testing, incident investigation, and migrations. Augment's Auggie CLI agent also boasts top performance on benchmarks like SWE-bench Pro, signaling its robust code generation and problem-solving capabilities.
Sourcegraph Cody, conversely, is an AI coding assistant built on top of Sourcegraph's established code intelligence platform. It leverages Sourcegraph's powerful Search API to provide multi-repository context, retrieving relevant code, symbols, and usage patterns from across entire enterprise codebases, often spanning 10 or more remote repositories. While it also offers agentic chat and inline editing, Cody's strength lies in its seamless integration with Sourcegraph's broader ecosystem (Code Search, Batch Changes, Code Insights), offering a unified experience for engineers already using the platform. Furthermore, Cody provides significant LLM flexibility, allowing enterprise admins to select from leading models like Claude, GPT, and Gemini, providing a degree of future-proofing and vendor choice.
Ultimately, Augment Code is ideal for enterprises seeking a deeply integrated, autonomous AI agent that can manage complex, end-to-end development tasks with unparalleled codebase understanding and stringent compliance. It's a complete, AI-first solution. Sourcegraph Cody is best suited for organizations that already rely on Sourcegraph's code intelligence and desire to augment their developers' capabilities with a highly contextual, flexible AI assistant that deeply understands their existing codebase infrastructure.
Frequently Asked Questions
QWhat is the main difference in how Augment Code and Sourcegraph Cody obtain codebase context?
Augment Code uses a proprietary Context Engine that semantically indexes 400,000+ files to build a persistent graph of functions, classes, and data flows. Sourcegraph Cody leverages Sourcegraph's existing Code Search API to retrieve relevant context from across multiple repositories indexed in the Sourcegraph platform.
QWhich tool is better for teams looking for a free or low-cost entry point?
Neither tool currently offers a free individual tier. Augment Code's Business plan starts at $100/month for up to 50 seats, which can be cost-effective for teams with variable usage. Sourcegraph Cody is now exclusively an enterprise product, requiring sales contact for pricing and typically carrying a higher per-user cost.
QCan Augment Code or Sourcegraph Cody be self-hosted for air-gapped environments?
Sourcegraph Cody offers self-hosted or BYO cloud deployment options, making it suitable for air-gapped or highly secure environments. Augment Code is primarily a closed-source SaaS offering, though Enterprise plans may offer custom cloud tenancy options.
QHow do their compliance certifications compare for enterprise use?
Augment Code holds the distinction of being the first AI coding assistant with ISO/IEC 42001 certification, alongside SOC 2 Type II, CMEK, and SIEM integration. Sourcegraph Cody is SOC 2 Type II compliant and offers features like SAML SSO, RBAC, and audit logs, with self-hosted options for enhanced security.
QWhich tool offers more flexibility in choosing underlying LLMs?
Sourcegraph Cody offers greater LLM flexibility, allowing enterprise administrators to select from various models including Anthropic's Claude, OpenAI's GPT models, and Google's Gemini, without being locked into a single provider. Augment Code uses its own integrated AI models, with no public information about user-selectable LLM options.