AI21, a leader in AI systems for enterprise, announced today the completion of its $208 million Series C funding at a valuation of $1.4 billion. Participation from additional new investors includes Intel Capital, the venture capital arm of Intel Corporation, and Comcast Ventures, the venture capital arm of Comcast Corporation, which joined previously announced investors. This new round of funding brings the company’s total capital raised to $336 million, accelerating AI21’s purpose-driven approach in the era of AI-first enterprises.
“A multi-disciplinary approach is needed to deliver AI to the end user,” said Anthony Lin, Corporate Vice President and Head of Intel Capital. “The AI21 full-stack offering combines foundation models with successful applications and operation tools that will help enterprises accelerate GenAI adoption to increase productivity and affect their bottom and top line.”
“We are impressed with the strong team at AI21 and their ability to scale quickly in a rapidly evolving Generative AI landscape,” said Allison Goldberg, SVP and Managing Partner, Comcast Ventures and Startup Engagement. “We look forward to seeing how AI21 will deliver enterprise solutions to strategically leverage this technology in a way that is meaningful and reliable.”
“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. 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,” said Ori Goshen, co-CEO and co-founder of AI21.
Task Specific Models Approach to Enterprise AI
General-purpose models, LLMs are a ‘jack of all trades’, built to offer unprecedented versatility and capable of tackling a broad variety of use cases and NLP tasks. In practice, enterprise customers only need a small number of NLP tasks to support an umbrella of business use cases. This means that enterprise customers are paying for capabilities they don’t need, while also dealing with reliability issues due to output hallucinations or confabulations and other nonsensical blunders caused by the lack of focus in LLM design.
AI21 Studio is a platform that provides API access to developers and businesses with top-tier natural language processing (NLP) solutions powered by AI21’s state-of-the-art language models. The platform’s Task-Specific Models, optimized Language Models (LLMs), are specifically engineered to excel in distinct natural language processing (NLP) capabilities. These models not only showcase exceptional performance in accuracy but also effectively reduce hallucinations, ensuring heightened reliability. Beyond their reliability, these Task-Specific Models cater to enterprises’ diverse needs, covering prevalent NLP capabilities such as contextual answers, summarization, and more. This versatility positions AI21 Studio as a comprehensive solution, offering top-tier NLP tools for a wide range of applications. For example, AI21’s Contextual Answers model, specifically designed for grounded question answering, is used by customers such as Clarivate, an analytics company, and One Zero digital bank to answer user queries using information based entirely on the organization’s body of data.
LLMs to AI Systems
AI21 is one of the few companies in the world that combines the development of proprietary large language models for enterprises with application development for consumers. AI21 achieves this through a neuro-symbolic architecture that combines large language models, external knowledge sources, and discrete reasoning.
“We will see an increasing shift in discussion to AI Systems that will define the next era in computing. By adopting a more comprehensive systems approach, our AI enriches LLMs with knowledge and reasoning, in addition to statistical inference. This enables us to define a flexible architecture with multiple LLMs, complemented by discrete knowledge and reasoning modules,” said Prof. Yoav Shoham, co-founder and co-CEO, AI21.