The author secured $100M for his enterprise-focused generative AI platform

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Investors haven’t yet tired of generative AI startups — especially those with obvious enterprise applications.

Notably, Author, which it describes as a “full-stack” generative AI platform for businesses, announced today that it raised $100 million in a Series B funding round led by ICONIQ Growth with participation from WndrCo, Balderton Capital and Insight. Partners, Aspect Ventures and author clients Accenture and Vanguard.

Co-founder and CEO May Habib says the new volume will fund Author’s development of “industry-specific” text-generating AI models, bringing Author’s total to $126 million and valuing the company between $500 million and $750 million post-money. TechCrunch.

“Many enterprises are still scratching the surface on generative AI, mostly building internal ‘CompanyX-GPT’-type applications,” Habib said via email. “Harder, more impactful use cases require more knowledge about recovery incremental creation, data gathering and cleaning, and workflow construction, and they realize that’s 90% of the work. That’s the part that makes Writer so easy — and all the data as well as the Large Language Model (LLM) can be hosted in an enterprise virtual private cloud, making it workable for enterprises.

Author A.I

The author’s models can be linked to the company’s “knowledge base”, providing them with additional context.

The author competes in a crowded field that includes not only OpenAI and its generative text AI rivals, such as Anthropic, AI21 Labs, and Mistral AI, but also enterprise-focused generative platforms such as Jasper, Cohere, and Typeface. All offer AI-powered tools to complete documents — or create them completely from scratch — from advertising to email campaigns, blog posts, flyers and copy for websites.

So what makes a writer different? Well, for one thing, it claims to have trained its fine-tunable models on non-copyrighted business writing, an important point at a time when the copyright status of AI-generated works remains somewhat unclear in the US. The author also asserts that his models are “smaller” than average and therefore more “cost-effective”; Transparent in the sense that customers can inspect the model’s code, features, and data; And never trained on customer data.

Like many of Author’s competitors, Author lets customers connect their models to business data sources to improve research, fact-checking, and question-answering capabilities. In addition, the author allows companies to apply regulatory, legal and brand rules to the model on its platform.

These capabilities have netted the author “hundreds” of customers, including Intuit, United Healthcare, UiPath, Spotify, L’Oreal, Uber and Accenture. The author, based in San Francisco with a team of 100 employees, claims to have grown revenue by 10x in the last two years.

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