Browserbase

Browserbase is hosted headless browser infrastructure built specifically for AI agents. Instead of standing up and managing your own fleet of Playwright or Puppeteer instances, you call the Browserbase API and get a browser session back. It handles authentication persistence, anti-bot fingerprinting, session recording, and concurrency. The companion Stagehand framework adds an AI-native control layer that understands pages semantically rather than relying on brittle CSS selectors. For teams building AI agents that need to interact with the web, Browserbase removes the infrastructure problem so you can focus on the agent logic.

Browser automation has been a solved problem for fifteen years. Selenium did it. Then Puppeteer did it better. Then Playwright did it better than Puppeteer. But all of them put the operational complexity squarely on you: your server, your browser instances, your crash recovery, your debugging when something fails mid-session and you're left wondering what the page looked like at the moment of failure.

Browserbase changes the question from "how do I run a browser" to "what do I want the browser to do." It's managed headless browser infrastructure sold as an API, built specifically for the era of AI agents that need to interact with the web. The operational stuff, session persistence, anti-bot fingerprinting, recording, concurrency, is their problem. Your problem is the agent logic.

Why browser infrastructure for AI agents is different

When a human navigates a browser, they handle a lot of implicit complexity without thinking about it. They log in once and stay logged in. If a page loads slowly they wait. If a CAPTCHA appears they solve it. If the layout changes across devices they adjust. When something goes wrong they can describe what happened.

AI agents interacting with browsers face all of those problems without any of the human adaptability that makes them manageable. A session cookie expires and the agent doesn't know it's been logged out. A CAPTCHA appears and the automation breaks. A page element moves and the CSS selector that worked yesterday silently fails. A browser instance crashes and the agent state is gone.

Traditional headless browser infrastructure doesn't solve these problems. It gives you a browser and leaves the rest to you. Browserbase is built around solving these problems for the AI agent use case specifically.

Authentication persistence means that when your agent logs into a web application, that session is stored and can be resumed across tasks without re-authenticating every time. For agents that need to work with private web applications (internal dashboards, SaaS tools, e-commerce backends), this is fundamental. Logging in on every task isn't just slow, it breaks two-factor authentication workflows that aren't designed to handle programmatic sign-in.

Session recording means every browser interaction is captured. You can replay exactly what the agent did and saw at any point in the session. When debugging why an agent failed to complete a task, you watch the recording rather than guessing from logs. For anyone who's tried to debug headless browser automation by reading Playwright output, this is a significant quality-of-life improvement.

Live view takes this further for active sessions. You can watch a browser session in real time as the agent is running it. This sounds like a nice-to-have until you're trying to understand why your agent keeps clicking the wrong button on a checkout page, and you can just watch it happen and immediately see the problem.

Stagehand: the AI-native control layer

Browserbase ships alongside Stagehand, an open-source framework from the same team that adds an AI layer on top of Playwright. Understanding the relationship between the two helps clarify what Browserbase actually sells.

Playwright is a tool for programmatic browser control. You write code that says "find the element with class submit-btn and click it." This works reliably when the page structure is stable and you know the selectors in advance. It breaks when pages change, when selectors are dynamic, or when you're building an agent that needs to interact with pages it's never seen before.

Stagehand replaces selector-based interaction with semantic description. Instead of page.click('.submit-btn'), you write await page.act("click the submit button"). An AI model interprets the instruction, looks at the actual page, and figures out what to click. If the submit button has a different class tomorrow, it doesn't matter. The agent described what it wanted, not how the page is structured today.

This is the right interface for AI agents. Agents are given goals, not implementation instructions. They shouldn't need to know CSS class naming conventions. Stagehand bridges the gap between "natural language goal" and "actual browser interaction" in a way that Playwright alone can't.

Stagehand runs on Browserbase's hosted infrastructure, which is where the two products come together. You use Stagehand's API to describe what you want, and Browserbase provides the reliable, persistent, observable browser sessions that Stagehand runs in.

Pricing that makes sense for the use case

Browserbase uses a usage-based model that fits how AI agents actually consume browser time. Agents don't run browsers 24/7. They spin up a session for a task, do the work, and exit. Paying for browser minutes rather than server uptime matches that pattern.

The free tier gives you enough to evaluate the product and build a prototype. The Starter plan at $39 per month is reasonable for a side project or early-stage product with moderate automation volume. At higher volumes, pricing scales with usage and concurrent session needs.

For comparison, running your own Playwright infrastructure at scale isn't free. You need servers, you need to manage browser instance limits, and you need an engineer who knows how to handle the failure modes. For teams where that engineering time costs more than the Browserbase fees, which is most product teams, the economics are straightforward.

The caveat is high-volume scraping use cases. If you're running thousands of browser sessions per day for data collection, the per-minute costs accumulate. At that scale, the calculus between self-hosted and Browserbase needs a spreadsheet, not a rule of thumb.

Where it fits against alternatives

The most direct competitors are other browser automation services and tools that try to solve the same problem from different angles.

Browser-Use is an open-source Python library that gives AI agents browser control. It's free to run but self-hosted, meaning you operate your own browser infrastructure. Browser-Use is excellent for developers who want maximum control and are comfortable with the ops work. Browserbase is for teams who'd rather pay to make the ops work disappear.

Skyvern is a full agent product built on AI browser automation. The comparison with Skyvern is different: Skyvern is an agent that executes specific workflow types (form filling, data extraction, web tasks). Browserbase is infrastructure that your own agents run on. They're at different layers. You might build something like Skyvern on top of Browserbase.

Multion is also a full agent product rather than infrastructure. Same distinction applies.

If you're building an AI agent product that needs browser capabilities, Browserbase is infrastructure. If you want a pre-built agent that handles browser tasks without you building anything, Skyvern or Multion are more direct solutions.

Building with Browserbase in practice

Getting started is straightforward. Install the SDK, get an API key from the Browserbase dashboard, and create a session:

import Browserbase from "@browserbasehq/sdk";
import { chromium } from "playwright-core";

const bb = new Browserbase({ apiKey: process.env.BROWSERBASE_API_KEY });
const session = await bb.sessions.create({ projectId: process.env.PROJECT_ID });
const browser = await chromium.connectOverCDP(session.connectUrl);

From there, your existing Playwright code runs against the hosted browser. The session recording, live view, and authentication persistence are active by default. You don't need to change your Playwright code to get the benefits, you just change where the browser lives.

For Stagehand integration, the setup is similar but you use Stagehand's semantic API instead of raw Playwright:

import { Stagehand } from "@browserbasehq/stagehand";
const stagehand = new Stagehand({ env: "BROWSERBASE" });
await stagehand.init();
await stagehand.page.goto("https://example.com");
await stagehand.page.act("fill in the search box with 'AI agents'");

The debugging workflow with live view is worth setting up from the start. Being able to watch your agent's browser sessions in real time catches problems that would take hours to debug from logs alone.

Who actually needs this

Developers building AI agents that interact with web applications are the primary audience. If your agent needs to log in to a SaaS tool, extract data from a web dashboard, fill out forms, or navigate a website that doesn't have an API, you need browser automation. Browserbase makes that automation more reliable and observable than self-hosted alternatives.

Teams building internal automation tools are another strong fit. Many internal business processes run through web applications without proper APIs: legacy systems, vendor portals, reporting dashboards. Agents that can operate these interfaces via browser are genuinely valuable, and Browserbase's authentication persistence makes that practical.

Developers who do light, occasional browser automation and are comfortable with Playwright on their own server don't need Browserbase. The overhead of the service isn't justified if you're running a handful of sessions per day with no reliability requirements.

The honest assessment

Browserbase solves a real problem that every team building web-capable AI agents eventually hits: running headless browsers reliably at scale is harder than it looks. Session management, authentication persistence, debugging, and anti-bot handling are collectively enough operational complexity to distract a small engineering team from building the actual agent logic.

The $39 Starter plan is priced right for early-stage products. The Stagehand integration is a genuine improvement over selector-based browser control for AI agent use cases. The session recording and live view features save meaningful debugging time.

The thing to watch is vendor dependency risk. Your agent's browser capability lives on Browserbase's infrastructure. If they have downtime, your agent has downtime. For most teams this is an acceptable trade given the operational burden of self-hosting, but it's worth having a contingency plan and keeping your Playwright code written in a way that could point at a local browser if needed.

For teams shipping AI agents that touch the web, Browserbase is the fastest path from prototype to something that actually works reliably. That's worth a lot.

Key features

• Managed headless browser sessions with no infrastructure to operate
• Persistent authentication state across sessions
• Built-in session recording and replay for debugging
• Playwright and Puppeteer compatible API
• Stagehand framework integration for AI-native browser control
• Live view for monitoring active browser sessions in real time
• CAPTCHA handling and anti-bot fingerprint management
• Concurrent session support for parallel automation workloads

Pros and cons

Who is Browserbase for?

• AI agents that need to log in and interact with web applications
• Web scraping pipelines that require JavaScript rendering and authentication
• QA automation for web apps where AI decides what to test
• Research agents that need to browse and extract information from live websites
• Workflow automation tools connecting to web apps without native APIs

Alternatives to Browserbase

If Browserbase isn't quite the right fit, the closest alternatives are browser-use , skyvern , and multion . See our full Browserbase alternatives page for side-by-side comparisons.