# Tabnine

> An AI code completion and chat assistant built around code privacy, self-hosting, and air-gapped enterprise deployment.

Website: https://www.tabnine.com

Tabnine is an AI coding assistant that runs as an extension inside your existing editor, providing inline code completions, chat across the development lifecycle, and agentic workflows. Its defining angle is control: where most assistants route your code through a vendor cloud, Tabnine is built to deploy on SaaS, in your VPC, on-premises, or fully air-gapped, with zero code retention so nothing you write trains a shared model.

It is aimed at teams that need AI in the editor but operate under real governance constraints — regulated industries, security-conscious orgs, and companies that simply cannot send proprietary source to a third party. Individual developers can use the extension too, but the product is engineered around the question of where your code goes and which model touches it.

## Highlights

- **Switchable models** — pick from 15+ LLMs including Claude, GPT, Gemini, and open models like Llama, Mistral, and Qwen; admins control which models are available per deployment.
- **Privacy by default** — zero data retention, and your code is never used to train models shared with other customers.
- **Flexible deployment** — run it as SaaS, in a VPC, on-premises, or fully air-gapped with no outbound connectivity.
- **In-editor chat** — ask about code, generate tests, write documentation, and get explanations without leaving the IDE.
- **Context Engine** — connect repositories (GitHub, GitLab, Bitbucket, Perforce) so suggestions reflect your organization's frameworks and coding standards.
- **Agentic workflows** — higher tiers add autonomous agents, a Tabnine CLI for terminal automation, and MCP tool integration.

## In an AI-assisted workflow

Tabnine fits into the editor you already use. You install the extension, sign in, and inline completions begin appearing as you type; the chat panel handles larger questions and multi-line generation. The decision that shapes everything is deployment — a team with sensitive code chooses an on-prem or air-gapped install, and from then on completions and chat are served from infrastructure they control.

> [!TIP]
> If your organization restricts which LLMs may handle source code, set the allowed model list at the admin level so every developer's editor inherits the same governance policy automatically.

Because models are switchable, a common pattern is to default to a fast model for inline completion and reach for a stronger one (such as Claude) in chat when generating tests or reviewing a tricky change.

## Good to know

Tabnine works in VS Code, JetBrains IDEs (IntelliJ, PyCharm, WebStorm, GoLand, Rider, CLion, and others), Eclipse, and Visual Studio 2022/2026; Xcode is not supported, and Vim/Neovim have only a legacy plugin with basic completions (no chat or agents). There is no free plan — both tiers are paid annual subscriptions — though a free trial is available to evaluate it. The Code Assistant platform ($39/user/month) covers inline completions, IDE chat, flexible deployment, and enterprise compliance (GDPR, SOC 2, ISO 27001). The Agentic platform ($59/user/month) adds the Context Engine, the Tabnine CLI, MCP tool integration, and autonomous agents.

> [!NOTE]
> The air-gapped and on-premises deployment options are the reason most teams choose Tabnine over a cloud-only assistant. If full code isolation is not a requirement for you, a simpler cloud tool may be a closer fit.

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_Source: https://agentscamp.com/tools/tabnine — Tool on AgentsCamp._