> For the complete documentation index, see [llms.txt](https://docs.tabnine.com/main/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.tabnine.com/main/welcome.md).

# Welcome

- [Overview](https://docs.tabnine.com/main/welcome/readme.md)
- [Architecture](https://docs.tabnine.com/main/welcome/readme/architecture.md)
- [Deployment Options](https://docs.tabnine.com/main/welcome/readme/architecture/deployment-options.md): Tabnine AI code assistant deployment options
- [Security](https://docs.tabnine.com/main/welcome/readme/security.md): Tabnine AI code assistant: Security
- [Privacy](https://docs.tabnine.com/main/welcome/readme/privacy.md): Tabnine AI code assistant: Privacy
- [Protection](https://docs.tabnine.com/main/welcome/readme/protection.md): Tabnine AI code assistant: Protection
- [Provenance and Attribution](https://docs.tabnine.com/main/welcome/readme/protection/provenance-and-attribution.md): Minimize IP liability of third-party models
- [Provenance & Attribution in Tabnine CLI](https://docs.tabnine.com/main/welcome/readme/protection/provenance-and-attribution-in-tabnine-cli.md): Provenance and Attribution (P\&A) enforcement for generated code now applies to the Tabnine CLI.
- [Personalization](https://docs.tabnine.com/main/welcome/readme/personalization.md): Tabnine AI code assistant: Personalization
- [Tabnine’s Personalization in Depth](https://docs.tabnine.com/main/welcome/readme/personalization/tabnines-personalization-in-depth.md)
- [Connection: Global Codebase Awareness](https://docs.tabnine.com/main/welcome/readme/personalization/connection-global-codebase-awareness.md)
- [AI Models](https://docs.tabnine.com/main/welcome/readme/ai-models.md): Tabnine AI code assistant: AI models
- [Integrations](https://docs.tabnine.com/main/welcome/readme/integrations.md)
- [Atlassian Jira Integration](https://docs.tabnine.com/main/welcome/readme/integrations/atlassian-jira.md): Tabnine AI code assistant: Atlassian Jira integration
- [System & Hardware Requirements](https://docs.tabnine.com/main/welcome/readme/system-requirements.md): Tabnine AI code assistant: System requirements
- [Tabnine Client & Deployment Requirements](https://docs.tabnine.com/main/welcome/readme/system-requirements/tabnine-client-and-deployment-requirements.md)
- [Tabnine Deployment Options](https://docs.tabnine.com/main/welcome/readme/system-requirements/system-requirements.md): Tabnine AI code assistant: System requirements
- [Additional Requirements & Features](https://docs.tabnine.com/main/welcome/readme/system-requirements/system-requirements-1.md): Tabnine AI code assistant: System requirements
- [Supported Languages](https://docs.tabnine.com/main/welcome/readme/supported-languages.md): Tabnine AI code assistant: Supported languages
- [Supported IDEs](https://docs.tabnine.com/main/welcome/readme/supported-ides.md): Tabnine AI code assistant: Supported IDEs
- [Tabnine Subscription Plans](https://docs.tabnine.com/main/welcome/readme/tabnine-subscription-plans.md)
- [Enterprise (SaaS)](https://docs.tabnine.com/main/welcome/readme/tabnine-subscription-plans/enterprise-saas.md): Tabnine AI code assistant: Enterprise subscription
- [Enterprise (private installation)](https://docs.tabnine.com/main/welcome/readme/tabnine-subscription-plans/enterprise-private-installation.md)
- [Support & Feedback](https://docs.tabnine.com/main/welcome/support-and-feedback.md): Tabnine AI code assistant support and feedback


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.tabnine.com/main/welcome.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.