Hyperbrowser – Scalable Browser Infrastructure for AI Apps
Hey HN! Excited to share a project we've been working on called Hyperbrowser. It’s a tool that makes scaling headless browsers ridiculously easy. It allows you to spin up hundreds of browser sessions in secure, isolated environments, with sub-second launch times. We automatically solve captchas, use residential proxies and manage concurrent sessions so that you can focus on your own business. The idea for Hyperbrowser came from our own struggles building AI apps and agents like sales tools, automations, and AI editors. Every project seemed to hit the same roadblock: interacting with the web.…
In plain words
Hyperbrowser provides scalable browser infrastructure for AI applications and agents. It enables developers to launch hundreds of isolated browser sessions with sub-second startup times, automatically handling captchas, residential proxies, and concurrent session management. Built to solve web interaction challenges in AI tools, sales automations, and agents, it lets users focus on their core business logic rather than browser infrastructure complexity.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hey HN! Excited to share a project we've been working on called Hyperbrowser. It’s a tool that makes scaling headless browsers ridiculously easy. It allows you to spin up hundreds of browser sessions in secure, isolated environments, with sub-second launch times. We automatically solve captchas, use residential proxies and manage concurrent sessions so that you can focus on your own business. The idea for Hyperbrowser came from our own struggles building AI apps and agents like sales tools, automations, and AI editors. Every project seemed to hit the same roadblock: interacting with the web. Whether we needed web data as input or web browsing as output, we faced constant challenges—getting blocked, setting up proxy services, solving captchas, and scaling everything in Kubernetes. On top of that, we had to build custom functions and services to convert websites into LLM-friendly markdown and crawl entire sites for relevant data. Keeping all of this running became a full-time job! To make this easy for everyone else we built Hyperbrowser. It packages everything we learned and built, with a nice frontend that gets rid of the boilerplate and lets you hit the ground running. Hyperbrowser works seamlessly with tools you already know, like Puppeteer, Playwright, or Selenium, while removing the hassle of infrastructure and scaling. If this sounds interesting, we’d love for you to give it a spin! You can sign up and start playing around with a free plan. Would love to hear your thoughts, feedback, or ideas! Check it out here at hyperbrowser.ai. If you have any questions at all feel free to reach out to me at [email protected]! Ideally share the website you'd like to scrape or automate. I can provide a script for it or we can create a custom API endpoint!
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 16d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 26d ago · cactuscompute.com
