Sourcegraph is a Code Search and Intelligence company founded in 2013 and based in San Francisco, United States. It has raised $223M in total funding, most recently a Series D in 2021 at a $2.6B valuation.
| Date | Stage | Amount | Valuation | Lead investors |
|---|---|---|---|---|
| Jul 13, 2021 | Series D | $125M | $2.6B | Andreessen Horowitz |
| Dec 3, 2020 | Series C | $50M | — |
| Sequoia Capital |
| Jul 28, 2020 | Series B | $5M | — | Felicis Ventures |
| Mar 3, 2020 | Series B | $23M | — | Craft Ventures |
| Oct 6, 2017 | Series A | $20M | — | Redpoint Ventures, Goldcrest Capital |
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Cody is an AI-powered coding assistant that uses repository-wide context and code graph intelligence to answer questions, generate code, explain codebases, and automate development tasks. It integrates directly into IDEs like VS Code and JetBrains, supporting features such as autocomplete, chat, test generation, and code editing. By leveraging deep codebase understanding rather than just local file context, Cody provides accurate, context-aware suggestions that help developers navigate large codebases, fix bugs, onboard faster, and improve code quality across enterprise teams.
Code Search is Sourcegraph's foundational code intelligence engine that enables developers to search, navigate, and understand code across any language and repository at scale. It supports regex, literal, and structural search patterns across monorepos and multi-repository environments. Code Search provides features like jump-to-definition, find references, documentation hover, and code graph navigation, making it indispensable for large enterprises managing millions of lines of code. It empowers developers to quickly find relevant code, trace dependencies, and refactor with confidence.
Deep Search is Sourcegraph's agentic code search capability that uses AI to interpret natural language queries and understand developer intent, going beyond keyword matching. It combines LLM-powered reasoning with Sourcegraph's code graph to retrieve semantically relevant code, even when the developer doesn't know exact function names or file locations. Deep Search is designed for complex, multi-step code understanding tasks, enabling developers and AI agents to discover relevant code, understand system behavior, and resolve issues across massive, unfamiliar codebases.
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