AI-powered coding tools like Cursor, Replit, Claude Code, and Lovable have accelerated developers’ ability to write code and ship products faster. Yet, app creators still face challenges in predicting how new features will perform before launch, relying mostly on beta releases or simulation software. Stepping into this gap, Blok—a startup recently out of stealth—enables developers to use AI to simulate diverse user personas to test app features and optimize user experience before deployment.
Founded in 2024 by serial entrepreneurs Tom Charman and Olivia Higgs, Blok has raised $7.5 million across two funding rounds. Its $5 million seed round was led by MaC Venture Capital, with support from individuals at Discord, Google, Meta, Apple, Snapchat, and Pinterest. The pre-seed round saw participation from Protagonist, Rackhouse, Ryan Hoover’s Weekend Fund, and Blank Ventures.
Marlon Nichols, managing GP at MaC Venture Capital, highlighted Blok’s unique value, saying, “We backed Blok because we believe product development is at an inflection point. Teams are shipping faster than ever, but they’re still making critical decisions based on A/B tests and gut instinct. Blok’s simulation engine flips that model — giving teams the ability to predict user behavior before a single line of code is written.”
Higgs explained the rising need for enhanced testing as interfaces grow more complex, noting, “We’re seeing people interact with technology through chat, through voice. So if you’re introducing visual UI [elements] into the mix, you have to make sure that you are not introducing unnecessary friction into a user’s workflow.”
Charman added that both startups and large enterprises face distinct challenges: smaller companies lack enough user cohorts for testing, while bigger firms want to avoid overloading apps with clunky features. “We are trying to reach a place where companies don’t need to release their features on an experimental basis and wait for a few weeks or months for results to show up,” he said.
Blok’s process begins when customers upload event log data from platforms like Amplitude, Mixpanel, or Segment. Using this data, Blok’s AI builds behavioral models and generates multiple user personas representing the app’s audience. Development teams then submit their Figma designs along with experiment hypotheses and user goals. Blok’s persona agents simulate user interactions repeatedly, providing detailed reports on outcomes, recommendations, and persona-specific insights. Users can even query the results via a chatbot.
Currently, Blok is operating behind a waitlist and working with early clients mainly in finance and healthcare—sectors where safe, accurate testing is critical. The startup charges through a SaaS model and is balancing compute costs while aiming to reach mid-single-digit millions in revenue this year as it expands its customer base.
