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    Home»Machine Learning & Research»Introducing Amazon Bedrock AgentCore Browser Device
    Machine Learning & Research

    Introducing Amazon Bedrock AgentCore Browser Device

    Oliver ChambersBy Oliver ChambersAugust 2, 2025No Comments12 Mins Read
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    At AWS Summit New York Metropolis 2025, Amazon Internet Providers (AWS) introduced the preview of Amazon Bedrock AgentCore browser instrument, a completely managed, pre-built cloud-based browser. This instrument allows generative AI brokers to work together seamlessly with web sites. It addresses two basic limitations: first, basis fashions (FMs) are educated on massive however static datasets and wish dynamic entry to present info when API entry isn’t available; second, organizations face vital challenges when trying to scale internet automation with AI for enterprise use instances.

    The event of agentic AI programs is transferring towards functions that may execute advanced, multistep duties. For these brokers to be efficient, they require entry to dynamic, real-time knowledge, notably from web sites and internet functions that don’t supply APIs or the place API integration could be advanced. Furthermore, as companies search to deploy AI-powered automation throughout their operations, they want options that may reliably scale with out the operational overhead of managing browser farms or fixing advanced concurrency points. The AgentCore Browser Device offers these capabilities, permitting brokers to carry out duties corresponding to automating analysis, streamlining operations, and interacting with web-based functions—all with the scalability, reliability, and safety of the AWS Cloud infrastructure. By offering a completely managed cloud-based browser, AWS addresses the crucial want for enterprises to deploy AI automation at scale throughout hundreds of concurrent periods, supporting use instances from customer support automation to large-scale knowledge assortment and evaluation, with out the normal complexity and useful resource constraints of self-managed browser automation frameworks.

    On this put up, we introduce the newly introduced Amazon Bedrock AgentCore Browser Device. We discover why organizations want cloud-based browser automation and the constraints it addresses for FMs that require real-time knowledge entry. We speak about key use instances and the core capabilities of the AgentCore Browser Device. We stroll by way of learn how to get began with the instrument.

    Why do you want the cloud-based AgentCore Browser Device?

    Conventional browser automation approaches have sometimes required vital infrastructure administration, safety issues, and growth experience. The introduction of a completely managed, cloud-based browser automation resolution addresses a number of crucial wants, together with simplified infrastructure administration, enterprise-grade safety, world availability and scaling, and value optimization. Organizations not have to provision, keep, and scale browser cases to help their automation wants. AWS now handles the advanced infrastructure necessities, so builders can give attention to constructing clever agent capabilities relatively than managing browser farms. Cloud-based browser automation offers remoted execution environments with AWS safety controls, lowering the chance of knowledge exfiltration or unauthorized entry which may happen in much less managed environments. With a cloud-based browser, you’ll be able to instantaneously deploy browser cases throughout the worldwide infrastructure of AWS in order that browser automation can scale. By providing browser automation as a managed service, organizations can use a consumption-based pricing mannequin as an alternative of sustaining always-on infrastructure, which may considerably scale back prices for intermittent workloads.

    Use instances for cloud-based browser automation

    Dealing with repetitive internet duties: With the introduction of Amazon Bedrock AgentCore Browser Device, organizations can now implement refined browser automation at scale. Cloud-based browser automation excels at minimizing guide execution of repetitive duties throughout internet interfaces. AI brokers can populate advanced internet varieties throughout a number of programs, validate entries, and keep compliance with enterprise guidelines. Brokers can navigate to inside dashboards, extract crucial metrics, and compile studies with out human intervention. For organizations managing massive user-generated content material domains, brokers can help human moderators by prescreening content material throughout a number of internet interfaces.

    AI powered analysis and intelligence gathering: With cloud-based browser automation, AI brokers turn out to be highly effective analysis assistants. They routinely observe associated web sites for pricing adjustments, new product launches, or content material updates with common monitoring. You need to use AI brokers to assemble and analyze shopper sentiment throughout numerous internet boards, evaluate websites, and social domains to tell product growth. With the AgentCore Browser Device, you’ll be able to create automated programs that repeatedly scan trusted info sources to maintain inside data bases present.

    Advanced workflow automation throughout programs: Many organizations function throughout quite a few internet functions that lack built-in workflows. Use the AgentCore Browser Device to automate buyer setup throughout a number of software-as-a-service (SaaS) programs when APIs are unavailable. This helps keep consistency and reduces error charges. You may monitor provider portals, stock programs, and logistics providers to keep up visibility throughout advanced provide chains. By automating account creation and permission settings throughout quite a few inside internet functions, worker onboarding turns into streamlined.

    Testing and high quality assurance: Cloud-based browser automation allows sturdy testing at scale. You need to use AgentCore Browser Device to validate person experiences and performance throughout completely different situations, units, and browsers in parallel. Deploy brokers to constantly work together with crucial enterprise functions and arrange alerts to your groups about efficiency points earlier than clients encounter them. With AgentCore Browser Device, you’ll be able to repeatedly check internet functions for accessibility compliance, safety vulnerabilities, or regulatory necessities.

    Legacy system integration: Many organizations keep legacy programs that lack trendy APIs. Allow trendy AI capabilities to work together with legacy internet functions that will be expensive to exchange or modernize. Apply clever automation to programs that had been by no means designed for programmatic entry. Because of this, you’ll be able to extract invaluable organizational knowledge trapped in older internet functions by way of common, automated harvesting.

    Core capabilities

    The Amazon Bedrock AgentCore Browser Device empowers AI brokers to work together with internet content material the identical approach people do, by way of a completely managed distant browser infrastructure that minimizes conventional complexity whereas delivering enterprise-grade safety and scalability.

    Internet interplay capabilities

    • Full navigation management throughout web sites and multipage workflows
    • Interplay with JavaScript-heavy functions and dynamic content material
    • Kind manipulation, together with textual content fields, dropdown menus, and file uploads
    • Humanlike interplay patterns corresponding to scrolling, hovering, and clicking

    Serverless browser infrastructure

    • Zero-management browser fleet with automated patching
    • Seamless scaling from single session to hundreds primarily based on demand
    • World deployment choices with usage-based pricing
    • Optimized efficiency with out infrastructure overhead

    Visible understanding

    • Full-page screenshots enabling AI comprehension of structure and content material
    • Visible aspect identification by look and place
    • Content material extraction from graphical parts
    • Decision and system emulation capabilities

    Human-in-the-loop integration

    • Actual-time interactive viewing and management for human operators
    • Session recording for evaluate, coaching, and compliance

    Enterprise-grade safety

    • Full session isolation for every browser occasion
    • AWS Id and Entry Administration (IAM) controls for entry administration
    • Ephemeral browser periods that reset after every use

    Advanced internet utility help

    • Full compatibility with trendy JavaScript frameworks
    • Authentication dealing with and session persistence
    • Processing of asynchronous content material and real-time updates
    • Clever interplay with advanced UI patterns

    Audit and compliance

    • Detailed interplay logging and session recording
    • Integration with AWS CloudTrail for complete monitoring

    Observability

    • Efficiency metrics on latency and useful resource utilization
    • Integration with Amazon CloudWatch for unified monitoring
    • Session document and replay for observability

    This complete set of capabilities bridges the basic hole between AI brokers and the human internet, enabling organizations to construct clever brokers that may perceive and work together with content material designed for people relatively than being restricted to API-based integrations.

    How an AI agent can use AgentCore Browser Device

    Amazon Bedrock AgentCore Browser runs in a safe, remoted containerized surroundings inside AgentCore, insulating internet exercise out of your native system. You may work together with the AgentCore Browser Device utilizing browser actuation libraries, corresponding to Playwright, or use AI agentic frameworks specialised for browser automation, corresponding to Amazon Nova Act and Browser Use. You too can combine browser automation as a instrument in a multi-agentic workflow.

    Amazon Nova Act or Browser Use works with the AgentCore Browser Device to take pure language directions from the person and convert them to actuations on the browser by following this workflow:

    1. The person sends a question corresponding to “seek for sneakers on Amazon”
    2. An agentic framework corresponding to Amazon Nova Act or Browser Use passes the question to the massive language mannequin (LLM)
    3. The LLM causes and generates directions in a structured output format (for instance, JSON encoded)
    4. The agentic framework maps these directions into browser actuation instructions (corresponding to Playwright, Puppeteer, or Selenium)
    5. The browser actuation instructions are executed on the AgentCore Browser over a safe WebSocket connection
    6. The response from the browser and a screenshot are despatched to the agent to motive additional

    This course of repeats till the unique job is full. The circulation is illustrated within the following diagram.

    Get began

    The Amazon Bedrock AgentCore Browser Device is obtainable to be used as we speak. For a group of open supply examples, go to the amazon-bedrock-agentcore-samples repository on GitHub.

    Conditions

    To make use of the Amazon Bedrock AgentCore Brower Device, it’s essential to full the next conditions:

    • Python 3.10+
    • Confirm your IAM person or function has the permissions to make use of AgentCore Browser:
    git clone https://github.com/awslabs/amazon-bedrock-agentcore-samples.git
    pip set up bedrock-agentcore 

    For browser visualization in your native machine, you want the BrowserViewerServer element within the repository you cloned at: 01-tutorials/05-AgentCore-tools/02-Agent-Core-browser-tool/interactive_tools

    You too can visualize the browser reside on the Amazon Bedrock AgentCore console at https://us-east-1.console.aws.amazon.com/bedrock-agentcore/builtInTools

    The next Python code demonstrates learn how to use the AgentCore Browser Device immediately with the Playwright library and the Amazon Bedrock AgentCore SDK. This instance initiates a safe browser session, connects to it, and automates an easy workflow by which it navigates to https://www.amazon.com and searches for a product.

    1. To get began with playwright:
    cd 01-tutorials/05-AgentCore-tools/02-Agent-Core-browser-tool

    1. Set up dependencies:
    1. Creator your playwright-based script:
    from playwright.sync_api import sync_playwright, Playwright, BrowserType
    from bedrock_agentcore.instruments.browser_client import browser_session
    from browser_viewer import BrowserViewerServer
    import time
    from wealthy.console import Console
    console = Console()
    def run(playwright: Playwright):
        # Create the browser session and maintain it alive
        with browser_session('us-west-2') as shopper:
            ws_url, headers = shopper.generate_ws_headers()
            # Begin viewer server
            viewer = BrowserViewerServer(shopper, port=8005)
            viewer_url = viewer.begin(open_browser=True)
            # Join utilizing headers
            chromium: BrowserType = playwright.chromium
            browser = chromium.connect_over_cdp(
                ws_url,
                headers=headers
            )
            context = browser.contexts[0]
            web page = context.pages[0]
            attempt:
                web page.goto("https://amazon.com/")
                console.print(web page.title())
                # Hold working
                whereas True:
                    time.sleep(120)
            besides KeyboardInterrupt:
                console.print("nn[yellow]Shutting down...[/yellow]")
                if 'shopper' in locals():
                    shopper.cease()
                    console.print("✅ Browser session terminated")
            besides Exception as e:
                console.print(f"n[red]Error: {e}[/red]")
                import traceback
                traceback.print_exc()
    with sync_playwright() as playwright:
        run(playwright)

    Alternatively, you’ll be able to construct a browser agent utilizing Amazon Nova Act to automate internet interactions:

    1. Join Nova Act at https://nova.amazon.com/act and generate an API key.
    2. In the identical Python digital surroundings:
    pip set up nova-act
    1. Creator your Nova Act primarily based script:
    import time
    from bedrock_agentcore.instruments.browser_client import browser_session
    from nova_act import NovaAct
    from wealthy.console import Console
    from browser_viewer import BrowserViewerServer
     
    NOVA_ACT_API_KEY = "YOUR_NOVA_ACT_API_KEY"
    console = Console() 
     
    def primary():
        attempt:
            # Step 1: Create browser session
            with browser_session('us-west-2') as shopper:
                print("r   ✅ Browser prepared!                    ")
                ws_url, headers = shopper.generate_ws_headers()
     
                # Step 2: Begin viewer server
                console.print("n[cyan]Step 3: Beginning viewer server...[/cyan]")
                viewer = BrowserViewerServer(shopper, port=8005)
                viewer_url = viewer.begin(open_browser=True)
     
                # Step 3: Use Nova Act to work together with the browser with NovaAct
                with NovaAct(
                        cdp_endpoint_url=ws_url,
                        cdp_headers=headers,
                        preview={"playwright_actuation": True},
                        nova_act_api_key=NOVA_ACT_API_KEY,
                        starting_page="https://www.amazon.com",
                    ) as nova_act:
                        end result = nova_act.act("Seek for espresso maker and get the main points of the bottom priced one on the primary web page")
                        console.print(f"n[bold green]Nova Act Consequence:[/bold green] {end result}")
                
                # Hold working
                whereas True:
                    time.sleep(1)
                 
        besides KeyboardInterrupt:
            console.print("nn[yellow]Shutting down...[/yellow]")
            if 'shopper' in locals():
                shopper.cease()
                print("✅ Browser session terminated")
        besides Exception as e:
            print(f"n[red]Error: {e}[/red]")
            import traceback
            traceback.print_exc()
     
    if __name__ == "__main__":
        primary()

    Alternatively, you’ll be able to run the tutorial notebooks within the Amazon Bedrock AgentCore GitHub repository.

    Pricing and availability

    Amazon Bedrock AgentCore gives versatile, consumption-based pricing with no upfront commitments or minimal charges. AgentCore Browser can be utilized independently of the opposite providers. You may attempt AgentCore providers at no further cost till September 16, 2025. After this date, AgentCore Browser Device can be charged primarily based on consumption. Billing is calculated per second, utilizing the best watermark of CPU and reminiscence utilization for that second, with a 1-second minimal. 128 MB minimal reminiscence billing applies. Community knowledge switch by way of buyer elastic community interfaces is billed at normal Amazon Elastic Compute Cloud (Amazon EC2) charges

    For extra details about pricing, go to Amazon Bedrock AgentCore (Preview) Pricing.

    Conclusion

    Amazon Bedrock AgentCore Browser Device marks a transformative development in AI-powered internet automation, providing organizations a completely managed, cloud-based browser resolution. AgentCore Browser Device addresses crucial limitations confronted by generative AI programs requiring real-time knowledge entry, enabling AI brokers to work together naturally with web sites by way of capabilities corresponding to full navigation management, visible understanding, and seamless integration with frameworks corresponding to Playwright and Amazon Nova Act. Through the use of this instrument, companies can now implement refined automation at scale throughout numerous use instances—from streamlining repetitive internet duties and conducting AI-enhanced analysis to automating advanced workflows and integrating with legacy programs—all whereas benefiting from the dependable cloud infrastructure of AWS that adapts to organizational wants with out the operational overhead of managing browser farms.

    Sources

    To be taught extra and begin constructing, go to the next assets:


    Concerning the authors

    Veda Raman is a Senior Specialist Options Architect for generative AI and machine studying at AWS. Veda works with clients to assist them architect environment friendly, safe, and scalable machine studying functions. Veda makes a speciality of generative AI providers like Amazon Bedrock and Amazon SageMaker.

    Rahul Sharma is a Senior Specialist Options Architect at AWS, serving to AWS clients construct and deploy, scalable Agentic AI options. Previous to becoming a member of AWS, Rahul spent greater than decade in technical consulting, engineering, and structure, serving to firms construct digital merchandise, powered by knowledge and machine studying. In his free time, Rahul enjoys exploring cuisines, touring, studying books(biographies and humor) and binging on investigative documentaries, in no specific order.

    Kishor Aher is a Principal Product Supervisor at AWS, main the Agentic AI group chargeable for growing first-party instruments corresponding to Browser Device, and Code Interpreter. As a founding member of Amazon Bedrock, he spearheaded the imaginative and prescient and profitable launch of the service, driving key options together with Converse API, Managed Mannequin Customization, and Mannequin Analysis capabilities. Kishor repeatedly shares his experience by way of talking engagements at AWS occasions, together with re:Invent and AWS Summits. Exterior of labor, he pursues his ardour for aviation as a normal aviation pilot and enjoys enjoying volleyball.

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