A change in language education technology has triggered fresh competition, as Forbes reported that Speak, an AI-powered tutoring platform built by two Thiel Fellowship alumni, surpassed $100 million in annualized revenue while expanding into new markets.
The startup achieved a $1 billion valuation during its growth, creating new challenges for established players in the language-learning industry.
AI Voice Tutor Expands From Seoul To Global Markets
Speak launched its operations in Seoul after co-founder Connor Zwick spotted significant demand for English education in the South Korean capital. He recognized a disconnect between student interest and the ineffective methods being taught. Traditional instruction focused on grammar memorization over conversational practice, a problem he aimed to solve with an AI system encouraging users to speak naturally.
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"English language learning there was like an obsession," Zwick said. "There was such latent demand."
The platform uses voice-based scenarios to guide learners through everyday situations such as ordering food, asking for directions, or chatting with classmates. Its engine runs on OpenAI technology, which gives users space to build custom practice scenes through simple prompts. Features like streak tracking and leaderboards help keep people engaged.
Speak delivers lessons in six languages: English, Korean, Spanish, Japanese, French, and Italian, and the app has reached roughly 15 million downloads since its debut. Most of the company's revenue comes from consumer plans. Users begin with free access, then move into paid tiers priced between $80 and $200 for deeper content.
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Speak Pushes Into Enterprise Training As Duolingo Continues To Dominate Language-App Revenue
The company added workplace plans in 2024 after individual users requested employer support. Roughly 500 firms, including KPMG and HD Hyundai, now offer Speak accounts to staff members in South Korea, Forbes reported. The service moved into the U.S. market in June after gaining traction in Japan and Taiwan.
Speak secured a total of $160 million from backers such as Khosla Ventures, Accel, and the OpenAI Startup Fund. Still, the revenue gap across the sector remains significant. Duolingo (NASDAQ:DUOL) generated $724 million last year and aims to reach $1.02 billion by year-end, with the app introducing AI-driven video sessions with the character Lily as part of a wider push toward automated language tutoring.
Zwick pointed to a different philosophy behind Speak, focusing on spoken comfort rather than grammar drills. Duolingo centers on vocabulary growth and structured rules, while Speak encourages active dialogue and clearer pronunciation.
Zwick said that users engage in spoken practice far more frequently on his platform compared to other language apps. He described mobile game-style learning tools as a way for people to feel less guilty about passing time on their phones, adding that his product aims to deliver a more serious learning experience.
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Thiel Fellows Apply Deep Learning Background To Education
Zwick met Speak co-founder Andrew Hsu through the Thiel Fellowship in 2012. Zwick had stepped away from Harvard University to build a study tool called Flashcards+, which later became part of the education company Chegg (NYSE:CHGG). Hsu left a Stanford University Ph.D. program a year earlier to join the fellowship.
The two spent time learning machine learning fundamentals by sitting in on classes at the University of California, Berkeley, and Stanford without formal enrollment. Those sessions included lectures taught by OpenAI co-founder John Schulman.
Khosla Ventures Partner and Managing Director Sven Strohband told Forbes that he evaluated early versions of the app in 2017. He recalled that the software recognized foreign accents with accuracy even before the company introduced full conversational features. He described the founders as early adopters of an AI-first approach.
The platform continues to advance as OpenAI models improve. Accent guidance and dynamic lesson adjustments now appear within the service, features that were unavailable during its early development.
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