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Tabnine infuses its AI coding assistant with enterprise-specific context

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Tabnine, the creator of the industry’s first AI-powered coding assistant for developers, is debuting new capabilities for its AI coding assistant that greatly increase the solution’s personalization capacity. Now offering code completions, code explanations, and documentation based on an organization’s specific code and engineering patterns, Tabnine continues to adhere to its mission of accelerating and streamlining the software development lifecycle through AI.

With technological advancement remaining in constant flux, engineering teams must meet the demands for applications and capabilities that align with the latest and greatest features—despite budgets and talent pools constantly shrinking.

Tabnine sees the answer lying in AI coding assistants that boost engineer productivity and efficiency; however, generative AI (GenAI) must yield extraordinarily relevant and accurate results in order to be useful, according to the company.

Tabnine’s latest AI coding assistant iteration acknowledges this growing tension for engineers, now exposing the assistant to the unique code and patterns of an enterprise for better, more tailored coding recommendations. By arming Tabnine’s AI coding assistant with an organization’s specific context, Tabnine increases the quality of code generation for engineers while offering more relevant information regarding coding questions, code syntax, and structure.

“Despite extensive training data, most AI coding assistants on the market today lack organization-specific context and domain knowledge, resulting in good but generic recommendations,” said Eran Yahav, co-founder and CTO of Tabnine. “Just as you need context to intelligently answer questions in real life, coding assistants also need context to intelligently answer questions. This is the driving force behind Tabnine’s new personalization capabilities, with contextual awareness to augment LLMs by providing all the subtle nuances that make each developer and organization unique.”

Tabnine’s latest AI coding assistant update culminates in the following features:

  • Context through local code awareness by accessing locally available data in a developer’s IDE
  • Connection to software repositories for global code awareness to increase code context and code recommendations
  • Customization of AI models for enriching the quality of assistant output
  • Commitment to advanced encryption and zero data retention with a private, customer-deployed version of Tabnine and robust privacy standards

To learn more about Tabnine, please visit https://www.tabnine.com/.

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