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Personalizing AI coding assistants to your organization

AI delivers highly relevant results for any engineering team through context, connection, coaching, and customization. 
 
Learn how you can get personalized AI models without sacrificing your privacy or security: 
  • Read about the 4 levels of progressive personalization Tabnine uses to optimize the performance of your AI coding assistant. 
  • Dive into how Retrieval Augmented Generation (RAG) and RAG with semantic memory create local and global code awareness for Tabnine. 
  • Explore how fine-tuning and Low-Rank Adaptation (LoRA) are used to create custom Tabnine AI models. 
  • Discover the best use cases and deployment options for a fine-tuned AI model. 
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