Enterprises are placing significant bets on generative AI to attain a competitive advantage, but obstacles to widespread adoption persist. According to a recent EY survey, businesses intending to embrace generative AI express concerns about the rapid advancements in the field and the proliferation of vendors claiming AI expertise, complicating their deployment plans.
Despite these challenges, global investments in “AI-centric” systems are projected to reach $154 billion by the end of the year, as per IDC forecasts. A poll by MIT Tech Review indicates that 50% of companies plan to increase budgets for data infrastructure and AI by over 25% in the coming year.
Startups, such as AssemblyAI, are capitalizing on this AI boom. AssemblyAI, an “applied AI” venture, reports a 200% growth in its paying customer base, reaching 4,000 brands. The company’s AI platform handles approximately 25 million API calls per day, with over 200,000 developers utilizing it to process more than 10 terabytes of data daily.
AssemblyAI’s success has attracted substantial investments, with Accel leading a $50 million funding round. Notable investors include former Salesforce co-CEO Keith Block, GitHub ex-CEO Nat Friedman, Daniel Gross, Insight Partners, and Y Combinator. AssemblyAI’s total capital raised now stands at $115 million.
Founded in 2017 by machine learning engineer Dylan Fox, AssemblyAI focuses on providing advanced and accurate speech-focused AI models through an easy-to-use developer platform. The company’s models perform tasks like speech-to-text, speaker identification, content moderation, and speech summarization through an API.
Despite the abundance of speech models from competitors like Deepgram, Rev, and Speechmatics, as well as tech giants such as Google Cloud, Azure, and AWS, Fox asserts that AssemblyAI’s models are more advanced, accurate, capable, and feature-rich.
Looking ahead, AssemblyAI plans to use a portion of the new funding to develop a “universal speech model” trained on over a petabyte of voice data, set to launch later in the year. The company also aims to expand its workforce by 50% to 75% next year, striving to become the “Stripe for AI models” by providing developers and product teams with easy access to state-of-the-art AI through a simple API.
