Tapping algorithms trained to understand the semantic models of code, the platform attempts to learn individual best practices and warn of deviation from those practices. Weiss noted that the company plans to hire new employees by the end of the year, expanding its workforce across the U.S. and Israel from 30 people to over 40. “Tabnine … was founded by Eran Yahav and myself 2017,” Weiss told TechCrunch in an email interview. Tabnine provides suggestions on every keystroke and also full line or function recommendations within integrated development environments including Android Studio, VSCode, IntelliJ, Webstorm, and Eclipse — driven by what Weiss describes as small, “code-native” AI models trained from the ground up on specific programming languages or areas. Tabnine currently has more than a dozen such models for popular languages, he said, as well as “community” models trained by ecosystem partners. Over the past year, Tabnine introduced over a dozen new AI models for Python, JavaScript, TypeScript, Java, and other languages, Weiss said, as well as integrations with GitHub, GitLab, and BitBucket.