Tabnine

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 LLMs by Anthropic, OpenAI, Google, Meta, Mistral, and others; 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, and Perforce in preview) 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.

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 are not on Tabnine's supported-IDE list (its Neovim client is marked not officially supported). As of September 2026 the pricing page lists no free plan: both tiers are paid annual per-user subscriptions, quoted through sales. 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. Model access supplied by Tabnine is billed on top, at the provider's token rate plus a 5% handling charge.