Sourcegraph is the code intelligence platform built for enterprise engineering teams managing large and highly complex codebases. As AI accelerates the pace of code generation, organizations face sprawling repositories that become increasingly difficult for both humans and agents to reason about, navigate, and maintain. Sourcegraph addresses this challenge by delivering deep code understanding and powerful search across every repository, code host, and line of code.

The platform centers on Deep Search, an agentic, natural language AI search capability that provides engineering teams with precise, context-aware answers about their entire codebase. Code Search enables fast, exhaustive search across millions of repositories on GitHub, GitLab, Bitbucket, Gerrit, Perforce, and more, equipped with filters, keyword operators, pattern matching, and regex support for finding exactly what is needed at enterprise scale.

Sourcegraph also exposes a Model Context Protocol server that provides AI coding agents such as Claude, Cursor, and Gemini with structured code graph knowledge, significantly improving agent accuracy and output quality in legacy and complex codebases. Batch Changes enables large-scale, cross-repository search-and-replace operations across all connected code hosts. Code Monitors allow teams to detect potential vulnerabilities, bad practices, and undesirable changes, then trigger automated actions or agents to notify and remediate.

Code Insights delivers AI-powered dashboards and high-level metrics to visualize trends and changes across the repositories that matter most. The platform is enterprise-ready with dedicated support, account managers, and support engineers, alongside SCIM-based user lifecycle management, SAML and OpenID Connect SSO, and fine-grained role-based access controls. Zero data retention ensures that LLM inference is never stored beyond operational requirements and never shared with third parties.