Tabnine
Overview
Tabnine's Enterprise Context Engine makes AI coding truly enterprise-ready. Instead of guessing from generic training data, it learns your organization's unique architecture, frameworks, and coding standards. It adapts to your mixed stacks and legacy systems, ensuring every suggestion aligns with your security, compliance, and performance requirements. By embedding enterprise knowledge directly into the coding experience, Tabnine transforms AI from a novelty into a governed, context-aware teammate that codes the way your enterprise works.
Use Cases
Enterprise-Grade Contextual Awareness
Tabnine's AI learns from your organization's unique architecture, frameworks, and coding standards to provide suggestions that align with your security, compliance, and performance requirements.
Flexible and Secure Deployment
Run Tabnine in any environment—secure SaaS, your own VPC, on-premises, or fully air-gapped—ensuring your code and IP never leave your control.
Centralized Governance and Control
Enforce policies, track usage, and manage costs across every user and team from a single, secure dashboard for complete visibility and accountability.
Pricing
Individual Plans
Includes:
- AI Code Completion (current line & multi-line, full functionality)
- In-IDE AI Chat supporting the entire SDLC, powered by leading LLMs from Anthropic, OpenAI, Google, Meta, Mistral, and more
- Support for all major IDEs
- Workflow AI agents: Test Case Agent, Jira Implementation Agent, Code Review Agent
- Autonomous agents with optional user-in-the-loop supervision
- Access to multiple tools via Model Context Protocol (MCP): Git, testing frameworks, linters, Jira, Confluence, databases, APIs, Docker, package managers, CI/CD systems
- Integration with Atlassian Jira Cloud & Data Center for enhanced AI responses
- Organizational Context Awareness: Understands organizational standards, connects to unlimited codebases (GitHub, GitLab, Bitbucket, Perforce P4), applies organizational coding standards, and provides relevant API/documentation/code examples
- Flexible Deployment: SaaS, VPC, self-hosted, or fully air-gapped deployments
- Zero code retention, full privacy, end-to-end encryption, and secure TLS communication
- SSO integration, enterprise-grade compliance (GDPR, SOC 2, ISO 27001, etc.), and license security protection
- Extensibility & Compatibility: Supports all major IDEs, LLMs, languages, cloud environments, legacy systems, and is extensible via MCP
- Controllability: Permissions management, usage scoping, auditing, governance controls, analytics, LLM access management, and code generation source tracking
- Support: Priority ticket support during business hours and team AI development training
- Unlimited usage with your own LLMs (self-hosted or cloud); for Tabnine-provided LLMs, pay token costs at provider rates plus a 5% service fee
Core Features
Standard Features
Advanced Features
Enterprise Context Engine
Adapts to your organization's unique architecture, frameworks, and coding standards, ensuring suggestions align with your security, compliance, and performance needs.
Flexible and Secure Deployment
Deploy Tabnine anywhere your code lives—as a secure SaaS, inside your VPC, on-premises, or in a fully air-gapped environment, giving you full control over your code and IP.
Centralized Governance and Control
Govern AI coding at scale by enforcing policies, tracking usage, and managing costs across all users and teams from a single, secure dashboard.
AI Models Support
Built-in Models
Anthropic
OpenAI
Meta
Mistral
Qwen
API Integration
Custom API
System Requirements
Supported Platforms
Windows 10+, macOS 12+, Linux (Kernel 6.2+)
API Support
Available for enterprise customers, with options for connecting to external models like Claude, GPT, and Gemini.
Compatibility
VS Code, Visual Studio 2022, Eclipse, and all JetBrains IDEs (IntelliJ, PyCharm, WebStorm, Rider, etc.)
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