Cody by Sourcegraph

Cody by Sourcegraph is a freemium AI coding assistant in the Coding Agents category, with plans starting at $0 (Free), $9/month per user (Pro), and custom Enterprise pricing. It fundamentally changes how developers interact with large codebases by leveraging Sourcegraph's code intelligence platform to provide full codebase context awareness across thousands of files and multiple repositories.

Sourcegraph, founded in 2013, has built one of the most widely adopted code intelligence platforms in the industry, used by enterprises managing codebases with millions of lines of code across hundreds of repositories. Cody extends that platform's indexing and search capabilities into an AI coding assistant that goes far beyond the single-file context window limitations of most competitors. By tapping into Sourcegraph's Code Search API, Cody retrieves relevant symbols, type definitions, usage patterns, and cross-repository references to construct rich context for every AI interaction.

Cody supports multiple frontier LLMs including Claude by Anthropic, GPT-4o by OpenAI, and Gemini by Google, giving developers and teams the flexibility to choose the model best suited to their task. Enterprise customers can bring their own API keys (BYOK) for additional cost control and model flexibility. This multi-LLM approach ensures that teams are never locked into a single provider and can adopt newer models as they become available.

The assistant is available as native IDE extensions for VS Code, JetBrains IDEs (IntelliJ, WebStorm, GoLand, PyCharm, and others), Visual Studio, and Neovim, providing a consistent AI coding experience across development environments. Features include AI-powered code completions with codebase context, natural language chat for code Q&A and generation, auto-edit suggestions that anticipate multi-line changes based on cursor position and editing patterns, and custom reusable prompts that teams can use to standardize workflows such as test generation, code review checklists, and documentation templates.

For enterprise environments, Cody provides robust governance and compliance capabilities. These include SSO and SAML integration, audit logging, repository-level context filters that let administrators exclude specific repositories from AI interactions, permission-aware context that respects existing access controls, and code attribution checking that compares AI-generated code against known open-source repositories to flag potential licensing issues before code is committed. Sourcegraph maintains SOC 2 compliance and offers zero data retention policies with LLM providers, along with self-hosted deployment options for organizations with strict data sovereignty requirements.

Sourcegraph has also developed Amp, a next-generation agentic coding product built on Cody's context engine. Amp extends Cody's capabilities into autonomous multi-step task execution, enabling developers to delegate complex coding tasks that span multiple files and repositories. Amp supports parallel subagent execution and team collaboration through shared threads, making it suitable for large-scale development workflows where multiple agentic tasks need to run concurrently.

Cody is particularly well-suited for large enterprise development teams working across monorepos or polyrepo architectures where cross-repository context is critical. Organizations in regulated industries such as banking, healthcare, and government benefit from Cody's enterprise security controls and compliance features. The tool also significantly reduces onboarding time for new developers joining large codebases, as Cody's full-context Q&A capabilities allow them to quickly understand unfamiliar code patterns, APIs, and architectural decisions without extensive manual code review.