Tabnine's Context Engine securely indexes your repositories, documentation, and APIs to understand your architecture.
Runs inference in your Kubernetes or private cloud. Connects securely to your internal services via MCP.
Developers collaborate with Tabnine through IDE and chat interfaces, where AI agents operate with full awareness of your codebase to plan, generate, and refine code.
Give AI access to enterprise data sources without exposing them externally. Automate domain-specific workflows.
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Hours, not weeks. Tabnine can be deployed inside existing infrastructure and connected to repositories within a day, minimizing IT overhead and avoiding third-party dependencies.
Nothing leaves your network. All processing, context building, and model inference occur within your controlled environment, ensuring code, designs, and artifacts remain classified and protected.
Improved quality, traceability, and review readiness. Engineering teams report faster cycle times, cleaner diffs, and reduced rework while maintaining compliance with program data management standards.