Sistava

Browser Use

AI browser automation library and cloud platform with stealth browsers, CAPTCHA solving, and session management.

About Browser Use

Browser Use is a popular open-source AI browser automation library and cloud platform. Its docs emphasize fast persistent browser automation, managed sessions, profiles, stealth browsers, CAPTCHA solving, and an MCP server for AI assistants. It is strong for developers who want control and a fast path to browser tasks. Sistava competes by packaging browser automation into an employee model with task management, memory, approvals, and business workflow coordination on top.

Platform details

Official website

What does Browser Use actually do?

Browser Use is an open source Python library that lets an LLM drive a real browser. You describe the task in plain English, and the agent reads the page, decides what to click, fills forms, and reports back. It is one of the most popular projects in this space, with around 95,000 GitHub stars. Under the hood it uses Playwright for the browser layer and a vision plus DOM strategy for navigation, so it does not rely on brittle CSS selectors. That is the main reason teams adopt it: when a site changes its layout, the agent often adapts without code edits. There is also a hosted Browser Use Cloud product with a free tier of 10 tasks per month and paid plans starting around $30 per month. The cloud runs the same library on managed infrastructure, so you skip the install and proxy setup. Sistava is a different shape. It is not a library you import or a hosted runtime for your scripts. It is an AI employee that owns a goal, runs Browser Use style actions when needed, and also handles email, CRM, and reporting around the browser work.

How much does Browser Use cost?

The open source library is free under an MIT style license. You pay only for the LLM provider you plug in, which is usually OpenAI, Anthropic, Google, or a local model through Ollama. A typical task burns 5 to 50 cents in model tokens, depending on page complexity and how often it re-plans. The hosted cloud starts at a free tier with 10 tasks per month and paid plans around $30 per month for higher volume, with extra task packs and concurrency tiers above that. The cloud price includes browser infrastructure, but you still pay for the underlying model. True cost shows up in two other places: engineering time wiring it into your stack, and tokens spent on retries when the agent gets confused. Vision based runs are token heavy compared to a hand crafted Playwright script. Sistava bundles the model, the browsing, the surrounding tools, and the agent reasoning into one credit quota. There is no separate task meter or LLM bill. The trade off is less control over which specific model runs each step.

When does Browser Use beat the alternatives?

Browser Use is the strongest pick when you want full control, want to self host, and care about avoiding vendor lock in. The MIT license, large community, and active issue tracker mean you can ship a custom agent without trusting a closed platform. It is also the cleanest starting point for engineers who want to learn how vision plus LLM browser agents work. The codebase is readable, the examples cover real sites, and you can swap models freely. That makes it popular in research and indie hacker projects. It is weaker as a finished product for non-engineers. There is no built in CRM, no task queue with retries, no team workspace, and no notion of an employee that remembers context across tasks. You build all of that yourself. Sistava is the opposite trade off. You give up Python level control of each step in exchange for an employee that already has memory, a workspace, scheduling, and integrations. For most founders the second shape ships faster.

Where does Browser Use fall short for production work?

Reliability is the honest weakness. Vision driven agents make mistakes on dense pages, modal dialogs, and multi step flows. Browser Use has improved a lot, but production users still wrap it in retry logic, fallback selectors, and human review for high stakes actions. Hosting is the other gap. The open source version assumes you run the browser, the proxies, and the queue yourself. Long jobs on protected sites need stealth tuning that the library does not solve out of the box. Privacy and compliance can also be a sticking point. The cloud privacy policy does not offer an opt out from model training on standard plans, so regulated teams default to self hosting and that puts the infrastructure burden back on you. Sistava removes that whole layer. The browsing runs on managed infrastructure, the retry and recovery logic is built in, and the employee maintains a memory of what it tried last time. The cost is less ability to inspect every browser step in raw Python.

How does Browser Use handle non-engineers and team workflows?

It does not. Browser Use is a developer library. There is no team workspace, no role based access, no shared task queue, and no built in CRM. A non engineer cannot meaningfully use it without a developer wrapping it in a UI first. Even the cloud version is mostly a hosted runtime for scripts. It runs the agent for you and shows logs, but it is not a place where a marketer can describe a campaign and watch an employee execute it across browser, email, and CRM. That is fine for the audience Browser Use is aimed at, which is engineers building automation inside their own product. It is not the right shape for a small founder team that just wants the work done. Sistava is built for the second case. The interface is a chat plus task board with a real AI employee on the other side. It is slower to customize for niche edge cases, but it ships work without code.

Comparison