Generative AI Startup AI21 Labs Adds $53M to Earlier $155M Funding Round
AI21 Labs has added $53 million to the $155 million Series C funding round announced in August, closing the oversubscribed round at $208 million. AI21’s total funding to date has now reached $336 million with a valuation of $1.4 billion. The round’s investors include Walden Catalyst, Pitango, SCB10X, b2venture, Samsung Next, and founder of (Intel-acquired) Mobileye Professor Amnon Shashua, with participation from Google and Nvidia.
AI21 Unicorn
The previous investment came as AI21 launched the enhanced and expanded iteration of generative AI writing and reading assistant Wordtune for individual and enterprise customers. The fresh capital is slated to support AI21’s focus on purpose-built enterprise generative AI solutions. It also comes as OpenAI faces a lot of uncertainty following CEO Sam Altman’s firing and rapid hiring by Microsoft, among other chaotic moves at the home of ChatGPT.
AI21’s generative AI portfolio includes a host of proprietary large language models, APIs, and the AI21 Studio for building generative AI apps. The company’s flagship product, Wordtune, began as a browser extension for generating text but has grown to incorporate Wordtune Read, which can summarize and analyze text, a host of rhetorical Spices, an iOS mobile app controllable by Siri, and Google Docs plug-in, even before the new version debuted. The new Wordtune platform encompasses features to draw both individuals and enterprises. It offers the ability to create templates for business documents, summarize information from mixed media (like a video and a document), and answer queries by drawing on linked databases, with citations included in the response.
“We’re extremely grateful for the support of our investors who believe in our deep technology expertise. This funding will enable AI21 to increase mindshare that one size doesn’t fit all, as enterprises look for unique partners that understand their specific needs,” explained AI21 CEO Ori Goshen. “Mass deployment of AI requires deep understanding of high-performance language models that can deliver better value and impact. Our approach is about designing AI with purpose, making it significantly more efficient than building from scratch, and much more cost effective.”
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