Code-generating AI platform Tabnine nabs $25M investment

Developers are ready to embrace AI tools, spurred by the dual promises of increased productivity and faster learning. According to one recent survey, 77% of devs feel favorably about using AI in their workflows and 70% claim to be using — or planning to use — AI coding tools this year.

Investors see potential in generative coding tools, too — particularly in what the tools can accomplish at enterprise scale. And this enthusiasm is translating to new financing for startups like Tabnine, which today announced that it raised $25 million in a Series B funding round led by Telstra Ventures with participation from Atlassian Ventures, Elaia, Headline, Hetz Ventures, Khosla Ventures and TPY Capital.

Dror Weiss and Eran Yahav co-founded Tabnine in 2012 to create a platform that infuses various steps in the software development lifecycle with generative AI. Yahav was — and still is — a professor at Technion (the Israel Institute of Technology), while Weiss is a Technion computer science graduate.

Among other coding tools powered by first- and third-party generative AI models, Tabnine offers Tabnine Chat, an AI “code assistant” that writes code and answers questions about organizations’ codebases — sort of like a ChatGPT for code.

Tabnine has competitors in GitHub Copilot and Amazon CodeWhisperer. But Weiss asserts that the company affords more control and personalization than rival systems, for example enabling customers to deploy its tools either on-premises or via a virtual private cloud.

“Our flexible architecture means we can switch [code-generating AI] models relatively easily and are thus not ever competing with the big generative AI model builders,” Weiss told TechCrunch in an email interview. “We future-proof as AI evolves and new models become available from other vendors; Tabnine can bring those models to developers wherever they code.”

Weiss also makes the case that Tabnine is less legally risky than its competition — at least from a commercial perspective.

Microsoft, GitHub and OpenAI are currently being sued in a class action lawsuit that accuses them of violating IP law by letting Copilot — which was trained on billions of examples of public code from the web, some under a restrictive license — regurgitate sections of copyrighted code without providing credit. Liability aside, some legal experts have suggested that AI like Copilot could put companies at risk if they were to unwittingly incorporate copyrighted suggestions from the tool into their production software.

Tabnine, Weiss notes, strictly uses AI models trained on code with permissive licenses — or works with customers to train models on their in-house codebases.

“We use a curated data set and know what has gone into it, so we have much better control and security,” Weiss said. “This is also the foundation for our customers using private models that are trained on their own code and run in their own virtual private clouds and datacenters.”

Tabnine’s approach seems to be working for it, certainly — which is all the more impressive in light of the collapse of one of its rivals, Kite, late last year. Tabnine claims to have over a million users and 10,000 customers — which, while short of Copilot’s roughly one million paying users and 37,000 corporate customers, is a respectable user base indeed.

Weiss says that the proceeds from the Series B — which brought Tabnine’s total raised to $55 million — will be put toward expanding Tabnine’s generative coding capabilities and further building out its sales and global support teams. Tabnine expects to end the year with 150 employees, up from ~60 today.

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