Speak builds a conversational AI language-learning app with mobile-first design (React, Swift, Kotlin) and LLM-powered tutoring (PyTorch, OpenAI). The tech stack reveals a company handling real-time user interaction (WebSockets, Redis) and training-data pipelines (Apache Airflow, BigQuery, Snowflake, dbt) — mirroring the dual challenge of scaling inference quality while managing the data infrastructure to improve model performance. Hiring velocity is decelerating while the backlog spans feature scaling, infrastructure reliability, and LLM output quality, indicating a post-launch product at growth stage.
Notable leadership hires: Growth Head, Sales Development Lead, Head of Growth
Speak is a mobile language-learning platform powered by conversational AI, launched in 2019 and operating across 15+ languages. The product targets two billion people globally attempting language acquisition, positioning one-on-one tutoring at scale as the core value proposition. The company operates a distributed team across San Francisco, Seoul, Tokyo, Taipei, and Ljubljana, with a 51–200 person headcount split across marketing, engineering, sales, product, and data functions. Current priorities center on geographic expansion (new markets and languages), customer success infrastructure, app-based video lessons, and scaling the platform to handle 10x user growth while maintaining LLM output quality.
Speak runs React and Node.js for web, Swift/SwiftUI and Kotlin/RxJava for mobile, PyTorch for model inference, and OpenAI for LLM capabilities. Backend uses PostgreSQL, Redis, Kubernetes, and GCP/AWS. Data pipelines rely on Apache Airflow, dbt, BigQuery, and Snowflake.
Speak is headquartered in San Francisco, CA, with distributed offices in Seoul, Tokyo, Taipei, and Ljubljana. The company employs 51–200 people across these locations.
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