AI-native note-taking app with handwriting, collaboration, and intelligent workflows
Goodnotes is a consumer-grade note-taking platform (24M+ users) that's now pivoting toward AI-native product capabilities and enterprise sales motion. The stack reveals a deep mobile-first engineering operation (iOS, Swift, SwiftUI, PyTorch, TensorFlow) paired with active hiring in sales (3 roles) and product (2 roles) — a shift toward go-to-market at scale. Pain points around enterprise pipeline generation and security policy scaling signal a move beyond consumer dominance into B2B territory.
Goodnotes is a note-taking application that combines handwriting input with digital collaboration and AI-powered features. The platform serves 24 million users across iOS and macOS ecosystems. Founded in 2011 and headquartered in London, the company employs 201–500 people. Recent project focus includes AI-native research workflows, targeted outbound campaigns, and creative workflow automation — suggesting expansion into professional and enterprise use cases alongside the core consumer base. Current hiring spans sales, product, and marketing roles across the UK, US, Germany, and Singapore.
Goodnotes runs on iOS, macOS, and Swift/SwiftUI for mobile development; Python, PyTorch, and TensorFlow for AI/ML; React and TypeScript for web surfaces; and C++, Rust, and WebAssembly for performance-critical components. Security and device management uses Okta, CrowdStrike, and Intune.
Recent projects include AI-native research workflows, AI-powered creative workflows, a new AI-native product launch, targeted outbound campaigns for enterprise sales, and thought leadership initiatives. Internal focus areas include support scaling and website design ownership.
Goodnotes's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.