Sold by: Code Creator
Deployed on AWS
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Launch a private AI competitor research and web monitoring server on AWS. Run browser based research, schedule recurring competitor scans, detect meaningful changes, and export executive reports using Amazon Bedrock. This product has charges associated with it for the provision and deployment of the application and AMI support.
Overview
Full AI Competitor Research and Web Monitoring Server by Code Creator gives strategy, product, marketing, sales, and research teams a private way to turn public competitor websites into repeatable intelligence inside their own AWS account.
The browser dashboard supports one time research tasks and recurring competitor monitors every 6, 12, 24, or 72 hours. The AI agent controls Chromium, limits browsing to approved domains when requested, and uses Amazon Bedrock through an EC2 IAM role. No long lived AWS access key or seller credential is included.
The Competitive Intelligence Command Center tracks active monitors, completed and failed runs, domains researched, 14 day activity, and the latest intelligence. Recurring reports classify results as Baseline, None, Minor, or Significant and can include evidence and recommended action. Customers can download individual reports as JSON or Markdown and export consolidated analytics as CSV for spreadsheets, archives, BI tools, and Amazon QuickSight workflows.
First boot detects the new public IP, generates a unique dashboard password, creates a secure HTTPS address, and starts the Docker application stack automatically on Ubuntu 26.04. Research history and monitor records remain on the EC2 instance so customers control access, backup, retention, and operating costs.
This is a repackaged open source software product wherein additional charges are applied for the deployment of the application and AMI support and compliance.
Highlights
- Launch ready private AI research. First boot generates unique credentials, configures HTTPS, and starts the full Docker stack automatically on Ubuntu 26.04.
- Recurring competitor monitoring and change detection. Schedule approved website scans every 6, 12, 24, or 72 hours using Amazon Bedrock through an EC2 IAM role.
- Executive intelligence and portable reports. Track activity, domains, failures, evidence, and recommended action, then export JSON, Markdown, or consolidated CSV.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 26.04
Deployed on AWS
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Pricing
Free trial
Try this product free for 5 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/hour |
|---|---|
t3.xlarge Recommended | $0.04 |
m7i.8xlarge | $0.04 |
m7i.4xlarge | $0.04 |
m7i.12xlarge | $0.04 |
m7i.large | $0.04 |
m7i.2xlarge | $0.04 |
t3.medium | $0.04 |
t3.2xlarge | $0.04 |
t3.large | $0.04 |
Dimensions summary
You pay by the hour based on the EC2 instance size you choose to run this pre-built server. The options fall into two families. The t3 instances (t3.medium, t3.large, t3.xlarge, and t3.2xlarge) are general-purpose burstable machines suited to lighter or variable workloads. The m7i instances (m7i.large, m7i.2xlarge, m7i.4xlarge, m7i.8xlarge, and m7i.12xlarge) offer more compute and memory for steadier demand. Within each family, the hourly rate rises as you move to larger sizes with more vCPUs and memory. Pick the size that matches your workload; there are no fixed tiers or add-ons.
Top-of-mind questions for buyers
You are billed for each hour an instance runs. One unit equals one running EC2 instance for one hour of the size you select. The software charge meters running time only. Stopped instances stop accruing software charges, though underlying AWS storage fees may still apply.
Both families bill per running hour with no upfront commitment. The t3 sizes use burstable CPU credits, so they suit lighter or variable workloads. The m7i sizes deliver steady compute and more memory for continuous demand. Each running instance meters independently at the rate for its chosen size.
Switching sizes is manual. You stop one instance and launch another at your chosen size. The hourly rate then reflects that new size, which carries more vCPUs and memory. There is no automatic upgrade and no tier crossover. You pay the rate of whichever size runs.
www.codecreator.com
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Vendor refund policy
You may cancel the AWS Marketplace subscription at any time. No contracts. Software charges already incurred are not refundable.
Legal
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Content disclaimer
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Version 3.6 introduces a private Competitive Intelligence Command Center, one time browser research, scheduled competitor monitors, recurring change detection, evidence and recommended action, JSON and Markdown downloads, consolidated analytics CSV export, Amazon Bedrock IAM role integration, automated HTTPS first boot setup, persistent task history, and validated Docker service health.
Additional details
Resources
Vendor resources
Support
Vendor support
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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