Companies are making significant investments in generative AI to gain a competitive advantage, although they face challenges in its adoption. According to a recent survey by EY, many businesses interested in embracing generative AI express concerns about the rapid advancements in the field and the proliferation of vendors claiming AI expertise, which complicates their deployment plans.
Despite these challenges, global investments in “AI-centric” systems are projected to reach $154 billion by the end of this year, according to IDC forecasts. Additionally, a poll by MIT Tech Review indicates that 50% of companies intend to increase their budgets for data infrastructure and AI by more than 25% in the upcoming year.
This growth trend is particularly benefiting startups like AssemblyAI, an “applied AI” venture that researches, trains, and deploys AI models for developers and product teams to integrate into their applications and services. AssemblyAI reports a 200% increase in its paying customer base, reaching 4,000 brands, and the company’s AI platform now handles approximately 25 million API calls daily. Furthermore, over 200,000 developers are actively utilizing the platform to process more than 10 terabytes of data each day.
Dylan Fox, the co-founder and CEO of AssemblyAI, emphasizes that AI models are continually improving and evolving. By leveraging AssemblyAI’s API platform, enterprises can focus on developing new AI products, applications, and workflows without the complexities of model development, training, and keeping pace with rapid innovations. The platform also alleviates the challenges of deploying AI models at scale, a task that is notoriously difficult and resource-intensive.
AssemblyAI’s success has garnered the attention of prominent investors, with Accel leading a $50 million funding round, supported by investors like former Salesforce co-CEO Keith Block, GitHub ex-CEO Nat Friedman, Daniel Gross, Insight Partners, and Y Combinator. This latest funding round brings AssemblyAI’s total capital raised to $115 million.
Founded by machine learning engineer Dylan Fox in late 2017, AssemblyAI was inspired by the Amazon Echo, which showcased the potential of advanced AI systems for voice applications. AssemblyAI specializes in AI models, particularly those focused on speech-related tasks such as speech-to-text conversion, speaker identification, content moderation, and speech summarization, all accessible through an API. Customers like Fireflies, a meeting transcription app, utilize AssemblyAI’s models for a wide range of content, including phone calls, Zoom meetings, podcasts, and videos.
While there are several speech models available from both startups and tech giants like Google Cloud, Azure, and AWS, AssemblyAI claims that its models are more advanced, accurate, capable, and feature-rich than the competition. The company is committed to continuous improvement and plans to launch a “universal speech model” later this year, based on training with over a petabyte of voice data. AssemblyAI also intends to expand its workforce, aiming for a 50% to 75% increase in its current 115-person team in the coming year.
Dylan Fox envisions AssemblyAI as the “Stripe for AI models,” where developers and product teams can easily access cutting-edge AI through a straightforward API. This approach allows customers to focus on developing specialized applications and internal workflows that leverage AssemblyAI’s proprietary data and continually improving speech AI models. With the recent funding round providing ample runway, the company anticipates strong demand and increased product adoption in light of the growing mainstream interest in AI.
