Introducing new, more highly personalized AI software recommendations
Blog post from Tabnine
Tabnine has introduced personalized AI coding assistance by enhancing its local and global code awareness capabilities, providing more accurate and context-aware recommendations for developers and engineering teams. This update allows Tabnine to tailor its code generation, explanations, and documentation suggestions to the specific coding environment and organizational codebase of its users, without compromising privacy due to advanced encryption and zero data retention policies. By integrating with developers' local IDEs and organizational code repositories, Tabnine can deliver results that align with project-specific syntax, semantics, and style, offering improvements in productivity and efficiency. The company uses retrieval-augmented generation (RAG) to enhance AI performance by combining local and global data with user prompts, ensuring that personalized recommendations are generated securely and privately. These improvements are available at no additional cost to Tabnine Pro and Enterprise users, with options for further customization and participation in a private preview for global code awareness.