Tabnine is an AI IDEs and Editors company founded in 2017 and based in Tel Aviv, Israel. It has raised $54.5M in total funding, most recently a Series B in 2023.
| Date | Stage | Amount | Valuation | Lead investors |
|---|---|---|---|---|
| Nov 8, 2023 | Series B | $25M | — | Telstra Ventures |
| Jun 15, 2022 | Series B | $15.5M | — | Qualcomm Ventures, OurCrowd, Samsung NEXT Ventures |
| Apr 27, 2020 | Series A | $12M | — | e.ventures |
| Jun 15, 2017 | Seed | $2M | — | Khosla Ventures |
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An AI-powered code completion tool that integrates with 15+ IDEs and supports 30+ programming languages. It provides real-time code suggestions, whole-line and full-function completions, and context-aware recommendations. Unlike generic AI coding tools, Tabnine can be trained on an organization's own codebase to deliver personalized suggestions that match internal coding standards and patterns. It deploys as a local IDE extension with models running on-device or via a secure VPC, giving enterprises control over their code data.
An AI-powered code assistant integrated directly into the IDE that functions like a ChatGPT-for-code. Developers can ask natural-language questions about their codebase, generate documentation, write unit tests, explain complex code segments, and refactor code. Tabnine Chat is grounded in the organization's own repositories, making answers more accurate and relevant than generic chat interfaces. It supports both first-party and third-party LLMs, allowing teams to choose the model that best fits their needs while keeping all interactions within the secure development environment.
The enterprise-grade deployment option of Tabnine designed for organizations with strict security, compliance, and governance requirements. It supports flexible deployment across SaaS, VPC, on-premises, and fully air-gapped environments, ensuring no code ever leaves the organization's infrastructure. Tabnine Enterprise integrates with existing tools, languages, and development workflows while enforcing organizational standards. It includes the Enterprise Context Engine that makes enterprise knowledge available to any AI agent or tool across preferred models, IDEs, and deployment environments.
A standalone product that provides the contextual layer needed to make AI coding reliable, safe, and effective in enterprise environments. It embeds enterprise knowledge—such as internal APIs, libraries, coding conventions, and architecture decisions—into the development workflow, making it available to any AI agent or tool. The Context Engine works across preferred models, IDEs, and deployment environments, ensuring that AI-generated code is grounded in the organization's actual codebase and practices rather than generic internet training data.
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