Sold by: Code Creator
Deployed on AWS
Turn long, sensitive PDFs into professional Word reports with exact page-cited findings inside your AWS account. Verified Evidence runs without optional AI services or GPU resources and includes private document review, report generation, and cost-aware EC2 shutdown capabilities.
Overview
Private Document Evidence Analyst by Code Creator helps audit, risk, procurement, compliance, and due diligence teams review long, sensitive documents using a core workflow that runs inside their own AWS account rather than requiring a shared SaaS document workspace.
Upload a PDF, choose Supplier Risk, Internal Audit, Executive Due Diligence, or a custom review, and receive a professionally formatted Word report containing task relevant findings with exact page references. The Verified Evidence workflow uses deterministic document processing and does not require optional AI services or GPU resources.
When additional interpretation is desired, optional AI analysis can be enabled through the appliance's advanced workflows. AI synthesis remains separate from verified source evidence. If optional AI synthesis does not pass the product output gate, Verified Evidence remains the authoritative result.
For unattended operation, the appliance includes report delivery and automatic EC2 shutdown capabilities to support cost-aware workflows. If required report delivery does not complete successfully, the instance remains running so the customer can correct the problem and retry.
The product runs inside the buyer's AWS account and preserves uploaded documents, reports, settings, and review history across normal EC2 stop and start cycles. It combines private deployment, complete document review, page cited evidence, professional reporting, optional AI analysis, and cost-aware automation in one AWS Marketplace appliance.
Highlights
- Page cited evidence reports from long PDFs - Review complete documents for supplier risk, internal audit, executive due diligence, or custom objectives and generate professional Word reports with exact source-page references.
- Private AWS deployment with optional AI - Run Verified Evidence inside your AWS account without optional AI services, IAM permissions, or GPU resources. Enable Amazon Bedrock or private Local Muse inference only when needed.
- Reduce EC2 compute costs with automatic shutdown - Deliver completed reports to a customer-controlled Amazon S3 bucket and automatically stop EC2 after successful processing and required report delivery, helping avoid paying for idle compute.
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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Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
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 |
|---|---|
g6.4xlarge Recommended | $0.25 |
m5.xlarge | $0.25 |
m5.8xlarge | $0.25 |
m5.24xlarge | $0.25 |
m5.4xlarge | $0.25 |
m5.2xlarge | $0.25 |
m5a.xlarge | $0.25 |
m5a.8xlarge | $0.25 |
m5a.4xlarge | $0.25 |
m5a.2xlarge | $0.25 |
Dimensions summary
You pay by the hour based on the AWS EC2 instance you choose to run this software. Pricing scales with instance size and family. Larger sizes (like xlarge up to 48xlarge) hold more compute and cost more per hour. The m5, m5a, m6a, m6i, m7a, and m7i families are general-purpose compute options. The g6 family adds GPU capacity for graphics or accelerated workloads. The t3 and t3a options offer burstable performance for lighter use. You pick one instance type and pay only for hours used.
Top-of-mind questions for buyers
You pay for the AWS EC2 virtual machine running this software. Each instance type maps to a set amount of CPU, memory, and (for g6) GPU capacity. You are billed for each hour that instance runs. Bigger sizes carry more compute and cost more per hour.
Software charges accrue only while your chosen instance runs. A fully stopped instance stops accruing hourly software fees. Note that stopped instances may still incur underlying AWS storage costs for attached volumes, which are separate from this software's hourly charge.
Yes. You are not locked to one instance type. You can stop your current instance and launch a different family or size, then pay that new type's hourly rate. Choose g6 for GPU workloads, t3 or t3a for lighter burstable use, and the m-families for general compute.
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
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA) .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
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
n/a
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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