Uindow

Prompt injection is the thing that actually worries me building browser-automation workflows day to day — most defenses I've seen are prompt-level ("don't follow embedded instructions"), which is brittle. Is your approach architectural (isolating what the model treats as data vs. instructions) or still model-level judgment calls?

Solid niche. What model is powering this under the hood, and how do you handle data privacy for sensitive inputs?

It runs entirely on your own machine and your own network, and every line of code it executes sits in plain sight in this repository.

The real-OS-input bet is the smart part here. Most automation stacks fire synthetic DOM events that sites can fingerprint, so driving genuine cursor movement and keystrokes should sail past a lot of the bot-detection that trips up Playwright and Puppeteer. The "every line sits in plain sight in this repo" stance is a nice trust signal too. One genuine question: how do you keep runs deterministic for CI when you depend on real OS-level input timing rather than synthetic events? Curious whether input-latency flakiness becomes a problem at scale.

Since it's a local LLM, have you found using it has a little latency? Soon we will have crazy AI chips for local llms so this is great planning for that

The real OS-level input approach is genuinely clever — most automation tools rely on synthetic events that modern sites fingerprint and block. What's your experience with headless vs headed mode for tasks requiring CAPTCHA solving? Also curious whether the signed Chromium requirement limits deployment in containerized environments like Docker. This looks like a great fit for AI agents that need to interact with sites defensively designed against bots.

The local-first approach is compelling, especially paired with visible source code and native file-dialog support. For teams using this in CI, I’d be interested in how you recommend balancing realistic OS-level input with repeatable tests — e.g., whether recorder output includes enough waits/assertions to keep runs stable across different machines.

Impressive approach to browser automation! Running on genuine OS-level input instead of synthetic page events is a smart move most automation tools break on sites that detect headless browsers. The prompt injection immunity is what really stands out here, especially for teams running scraping or QA pipelines where untrusted content

The real-OS-input approach is a genuinely clever move. Most automation stacks rely on synthetic DOM events that modern anti-bot systems (like Cloudflare or Akamai) can easily fingerprint and block, so driving a real cursor and actual keystrokes should bypass a lot of those hurdles. That said, from a QA and stability perspective, I have one question regarding CI/CD pipelines: How do you maintain determinism when relying on real OS-level input timing rather than synthetic events? Does input latency flakiness become an issue at scale, and are there any recommended best practices for balancing "realistic input" with "test speed" in a headless environment?

Clever approach. UI feels solid and FTUE is amazing.

Good you can do much better

This is the kind of startup I like seeing. Wishing you and your team plenty of growth. If hiring becomes a challenge, check out Axisure. We connect startups with equity-based talent. axisure.xyz